Exploring Psychosocial, Cognitive, and Behavioural Factors in Supply Chain Operations: A Human-Centric Approach

RÉSUMÉ: L’industrie 4.0 (I4.0) transforme les lieux de travail industriels modernes grâce à l'adoption de technologies avancées telles que l'intelligence artificielle (IA), l'analyse de données en temps réel et l'automatisation. Ces technologies modifient de manière significative les rôles et les responsabilités des travailleurs, introduisant à la fois des opportunités et des défis. D'un côté, ces avancées peuvent améliorer la productivité et offrir aux travailleurs la possibilité de s'engager dans des tâches plus significatives et stimulantes. D'un autre côté, elles introduisent des défis tels que des exigences cognitives accrues, l'insécurité de l'emploi, des tâches standardisées et monotones, ainsi que le besoin de développement continu des compétences. Ces derniers peuvent impacter de façon significative le bien-être, la rétention, la performance, la motivation et la satisfaction au travail à moyen ou long terme. Malgré de nombreuses recherches sur les aspects techniques des technologies de l'I4.0, il y a un manque notable d'études abordant les impacts psychologiques, en particulier les dimensions psychosociales, cognitives et comportementales de ces technologies sur les travailleurs. Ainsi, l'objectif général de cette thèse est d'évaluer l'impact des technologies de l'I4.0 sur les dimensions psychologiques de l'interaction humain-technologie au sein des opérations de la chaîne d'approvisionnement. Pour atteindre cet objectif, la thèse utilise une méthodologie multifacette, incluant des revues systématiques de la littérature, des études expérimentales et des études de terrain longitudinales. La première étape consistait en une revue systématique visant à identifier et caractériser les résultats psychosociaux, cognitifs et comportementaux liés aux technologies de l'I4.0, à analyser leurs antécédents et leurs conséquences et à développer un plan de recherche pour les futures recherches centrées sur l'humain. Cette revue a permis d’identifier plusieurs lacunes importantes ouvrant la voie aux études expérimentales et longitudinales subséquentes. Premièrement, il existe peu de recherche évaluant les composantes psychosociales de l'interaction humain-IA, telles que la motivation des travailleurs, l'autonomie et le sens du travail, sans compter l’absence d'études expérimentales sur ces variables. Deuxièmement, la recherche sur les aspects cognitifs de l'interaction humain-IA, en particulier en ce qui concerne l'attention et la prise de décision lorsque les opérateurs humains doivent intervenir, est rare. Enfin, il y a un manque significatif de recherches longitudinales sur l'impact global de la technologie sur les travailleurs. Pour combler la première lacune, une étude expérimentale a été menée pour évaluer les impacts psychosociaux de différents niveaux de soutien à la décision par l'IA sur la motivation, l'autonomie, le sens du travail et l'engagement des travailleurs. Cette étude a révélé que l'automatisation partielle de la sélection des décisions, qui équilibre l'assistance de l'IA avec le contrôle humain, conduit à de meilleurs résultats psychosociaux par rapport à l'automatisation complète, améliorant la motivation, l'engagement, le sens du travail et l'autonomie des travailleurs. Pour combler la deuxième lacune, une autre étude expérimentale s'est concentrée sur l'automatisation par l'IA pendant la formation examinant comment différents niveaux de soutien à la décision par l'IA pendant la formation de travailleurs impactent l'acquisition de compétences, l'engagement, la motivation et les capacités de prise de décision. Les résultats ont indiqué que l'automatisation partielle de la sélection des décisions pendant la formation améliore significativement l'acquisition de compétences, la motivation et maintien des niveaux plus élevés d'engagement cognitif chez les travailleurs. Pour combler la dernière lacune, une étude de terrain longitudinale a été menée pour évaluer les impacts psychosociaux, cognitifs et comportementaux réels des technologies de l'I4.0 en examinant spécifiquement les facteurs de risque situationnels introduits par les technologies avancées dans la livraison du dernier kilomètre. En utilisant une approche multi-méthodes incluant des mesures physiologiques, perceptuelles et observationnelles, cette étude a révélé que les conditions de livraison telles que le secteur de livraison, la durée du quart de travail et la pression temporelle affectent significativement la fatigue, le stress, l'attention et le comportement de conduite à risque des conducteurs, soulignant ainsi l'importance de considérer comment les choix de conception technologique impactent les travailleurs. En conclusion, l'exploration des facteurs humains dans l'intégration des technologies avancées dans les opérations de la chaîne d'approvisionnement a produit des résultats généralisables à d’autres contextes que ceux étudiés. Ces constats ont des implications pour l'avenir du travail, la conception technologique et la gestion organisationnelle, faisant progresser la vision d'une Industrie 5.0 centrée sur l'humain. En somme, les résultats démontrent que l'automatisation équilibrée et une conception réfléchie des systèmes d'IA peuvent améliorer de manière significative les dimensions psychosociales, cognitives et comportementales de l'interaction humain-technologie. Cet équilibre améliore non seulement le bien-être individuel, mais se traduit également par des niveaux plus élevés de motivation, d'engagement et de performance, entre autres. En favorisant des environnements qui priorisent le bien-être et le développement des travailleurs, l'Industrie 5.0 peut soutenir un avenir durable et inclusif où la technologie et l'humanité progressent ensemble. Cette thèse souligne également l'importance critique de la recherche interdisciplinaire, multi-méthodes et intersectorielle pour comprendre les impacts multifacettes des nouvelles technologies sur les travailleurs humains. Intégrer des perspectives de domaines tels que l'ergonomie, la psychologie organisationnelle, les sciences cognitives et le génie industriel est essentiel pour développer une vue d'ensemble de la manière dont les travailleurs s'adaptent aux changements dans leur environnement de travail. Cette approche assure que la conception et la mise en œuvre des nouvelles technologies et des processus de travail soient informées par une compréhension profonde de la réalité des travailleurs, promouvant ultimement le bien-être humain et faisant avancer la vision d'une Industrie 5.0 centrée sur l'humain. ABSTRACT: Industry 4.0 (I4.0) is reshaping modern industrial workplaces through the adoption of advanced technologies such as artificial intelligence (AI), real-time data analytics, and automation. These technologies significantly alter worker roles and responsibilities, introducing both opportunities and challenges. On the positive side, these advancements can improve productivity and create opportunities for workers to engage in more meaningful and stimulating tasks. However, they also introduce challenges such as increased cognitive demands, job insecurity, standardized monotonous tasks, and the need for continuous skill development. These dual-edged impacts of technology have significant medium- to long-term effects on the psychological dimensions of workers, including employee well-being, retention, performance, motivation, and job satisfaction. Despite extensive research on the technical aspects of I4.0 technology, there is a notable lack of studies addressing the psychological impacts—specifically the psychosocial, cognitive, and behavioral dimensions—of these technologies on workers. As such, the general objective of this thesis is to assess the impact of I4.0 technology on the psychological dimensions of human-technology interaction within supply chain operations. To achieve this objective, the thesis employs a multifaceted methodology, including systematic literature reviews, experimental studies, and longitudinal field studies. The first step was a systematic review aimed at identifying and characterizing the psychosocial, cognitive, and behavioral outcomes related to I4.0 technology, analyzing their antecedents and consequences, and developing a roadmap for future human-centered research. This review identified several critical gaps, which paved the way for the subsequent experimental and longitudinal data collections. First, there is a lack of evaluation of the psychosocial components of human-AI interaction, such as worker motivation, autonomy, and job meaningfulness, compounded by the absence of experimental studies on these variables. Second, research on the cognitive aspects of human-AI interaction, particularly in attention and decision-making when human operators must intervene, is insufficient. Finally, there is a significant gap in longitudinal and field research on the overall impact of technology on workers. To address the first gap, an experimental study was conducted to evaluate the psychosocial impacts of different levels of AI decision support on worker motivation, autonomy, job meaningfulness and engagement. This study found that partial automation of decision selection, which balances AI assistance with human control, leads to better psychosocial outcomes compared to full automation, enhancing worker motivation, engagement, job meaningfulness, and autonomy. Addressing the second gap, another experimental study focused on AI automation during training, examining how different levels of AI decision support during training sessions impact skill acquisition, engagement, motivation, and decision-making capabilities. The findings indicated that partial automation of decision selection during training significantly improved skill acquisition and motivation and maintained higher levels of cognitive engagement among workers. To fill the final gap, a longitudinal field study was conducted to assess the real-world psychosocial, cognitive, and behavioral impacts of I4.0 technologies, specifically examining situational risk factors brought forward by advanced technology in last-mile delivery. Using a multi-method approach that included physiological, perceptual, and observational measures, this study revealed that delivery conditions such as delivery area, shift length, and time pressure significantly affect driver fatigue, stress, attention, and risky driving behavior, emphasizing the importance of considering how technology design choices impact workers. The comprehensive exploration of human factors in the integration of advanced technologies in supply chain operations has yielded insights that extend beyond the immediate findings of the individual studies. These insights hold implications for the future of work, technological design, and organizational management, driving forward the vision of a human-centric Industry 5.0. In short, the findings demonstrate that balanced automation and the thoughtful design of AI systems can significantly enhance the psychosocial, cognitive, and behavioural dimensions of human-technology interaction. This balance not only improves individual well-being but also translates into higher levels of motivation, engagement, and performance, among others. By fostering environments that prioritize the well-being and development of workers, Industry 5.0 can achieve a sustainable and inclusive future where technology and humanity advance together, ensuring that as technology evolves, it does so in a way that uplifts and empowers humanity. This thesis also underscores the critical importance of interdisciplinary, multi-method, and cross-domain research in comprehending the multifaceted impacts of new technologies on human workers. Integrating insights from fields such as ergonomics, organisational psychology, cognitive science, and industrial engineering is essential to develop a comprehensive view of how workers adapt to changes in their work environment. This approach ensures that the design and implementation of new technologies and work processes are informed by a deep understanding of workers’ reality, ultimately promoting human well-being and driving the vision of a human-centric Industry 5.0

The Use of Eye-tracking in Information Systems Research: A Literature Review of the Last Decade

Eye-trackers provide continuous information on individuals’ gaze behavior. Due to the increasing popularity of eye- tracking in the information systems (IS) field, we reviewed how past research has used eye-tracking to inform future research. Accordingly, we conducted a literature review to describe the use of eye-tracking in IS research based on a sample of 113 empirical papers published since 2008 in IS journals and conference proceedings. Specifically, we examined the methodologies and experimental settings used in eye-tracking IS research and how eye-tracking can be used to inform the IS field. We found that IS research that used eye-tracking varies in its methodological and theoretical complexity. Research on pattern analysis shows promise since such research develops a broader range of analysis methodologies. The potential of eye-tracking remains unfulfilled in the IS field since past research has mostly focused on attention-related constructs and used fixation count metrics on desktop computers. We call for researchers to utilize eye-tracking more broadly in IS research by extending the type of metrics they use, the analyses they perform, and the constructs they investigate

Sensorless Control with Switching Frequency Square Wave Voltage Injection for SPMSM with Low Rotor Magnetic Anisotropy

High-frequency signal injection sensorless algorithms are widely studied and used for rotor angle estimation in PMSM at low speed or standstill. One of the main drawbacks of such methods is the acoustic noise connected to the voltage injection. In order to minimize this problem, it is advisable to increase the frequency of the injected signal. Thus, many studies focus on square-wave injection at the switching frequency, which is the maximum theoretical frequency. Since these methods exploit the rotor magnetic anisotropy, it is relatively easy to use them in interior PMSMs, where the rotor anisotropy is high. On the contrary, it is hard to exploit them in surface PMSMs, which have an almost symmetric rotor, although a low rotor magnetic anisotropy is still present. In this paper, a sensorless algorithm with switching frequency squarewave injection is developed for surface PMSMs. To increase the signal-to-noise ratio, current oversampling is exploited. The benefits of such a technique are demonstrated with experimental results on a 2 Nm SPMSM

Electrical-Loss Analysis of Power-Split Hybrid Electric Vehicles

The growing development of hybrid electric vehicles (HEVs) has seen the spread of architectures with transmission based on planetary gear train, realized thanks to two electric machines. This architecture, by continuously regulating the transmission ratio, allows the internal combustion engine (ICE) to work in optimal conditions. On the one hand, the average ICE efficiency is increased thanks to better loading situations, while, on the other hand, electrical losses are introduced due to the power circulation between the two electrical machines mentioned above. The aim of this study is then to accurately evaluate electrical losses and the average ICE efficiency in various operating conditions and over different road missions. The models used in this study are presented for both the Continuously Variable Transmission (CVT) architecture and the Discontinuously Variable Transmission (DVT) architecture. In addition, efficiency maps of the main components are shown. Finally, the simulation results are presented to point out strengths and weaknesses of the CVT architecture

A Motivational Perspective on the Personalization of Gamification

The gamification of information systems has seen success in a variety of contexts. However, research has shown that the degree to which gamification is successful varies between individuals. The current paper evaluates the effectiveness of personalized gamification in a warehouse management context. Additionally, this paper explores why personalized gamification can be more successful than non-personalized gamification. Twenty-six subjects participated in a within-subject laboratory experiment in which goal setting and feedback game elements were integrated into a wearable management information system to examine their effect on user performance in a warehouse picking task. The effectiveness of personalized gamification was evaluated by categorizing participants into user types using the HEXAD model and examining performance across conditions and user types. Results show that user type significantly affects the relationship between game elements and user performance. This paper takes a step forward in exploring the motivational mechanisms that explain the efficacy of personalized gamification

Surface Permanent Magnet Synchronous Motors’ Passive Sensorless Control: A Review

Sensorless control of permanent magnet synchronous motors is nowadays used in many industrial, home and traction applications, as it allows the presence of a position sensor to be avoided with benefits for the cost and reliability of the drive. An estimation of the rotor position is required to perform the field-oriented control (FOC), which is the most common control scheme used for this type of motor. Many algorithms have been developed for this purpose, which use different techniques to derive the rotor angle from the stator voltages and currents. Among them, the so-called passive methods have gained increasing interest as they do not introduce additional losses and current distortion associated instead with algorithms based on the injection of high-frequency signals. The aim of this paper is to present a review of the main passive sensorless methods proposed in the technical literature over the last few years, analyzing their main features and principles of operation. An experimental comparison among the most promising passive sensorless algorithms is then reported, focusing on their performance in the low-speed operating region

Should Gamification be Personalized? A Self-deterministic Approach

Information system (IS) gamification has been successful in many contexts. Yet, research has shown gamification’s success to vary between individuals. In this paper, we compare personalized versus non-personalized gamification in a warehouse management setting. We devised a 26-participant within-subject experiment in which we programmed goal setting and feedback gamification elements into a wearable warehouse management system to evaluate the effectiveness of personalized gamification in terms of user performance. We examined the extent to which personalized gamification succeeded by categorizing participants into one of six user types through the HEXAD scale and then evaluating their performance time and errors across user types and conditions. We found that personalized gamification is more effective than non-personalized gamification. We present and discuss the motivational mechanisms through which personalized gamification can be more effective

Differentiation impairs Bach1 dependent HO-1 activation and increases sensitivity to oxidative stress in SH-SY5Y neuroblastoma cells

Neuronal adaptation to oxidative stress is crucially important in order to prevent degenerative diseases. The role played by the Nrf2/HO-1 system in favoring cell survival of neuroblastoma (NB) cells exposed to hydrogen peroxide (H2O2) has been investigated using undifferentiated or all-trans retinoic acid (ATRA) differentiated SH-SY5Y cells. While undifferentiated cells were basically resistant to the oxidative stimulus, ATRA treatment progressively decreased cell viability in response to H2O2. HO-1 silencing decreased undifferentiated cell viability when exposed to H2O2, proving the role of HO-1 in cell survival. Conversely, ATRA differentiated cells exposed to H2O2 showed a significantly lower induction of HO-1, and only the supplementation with low doses of bilirubin (0,5-1 \uce\ubcM) restored viability. Moreover, the nuclear level of Bach1, repressor of HO-1 transcription, strongly decreased in undifferentiated cells exposed to oxidative stress, while did not change in ATRA differentiated cells. Furthermore, Bach1 was displaced from HO-1 promoter in undifferentiated cells exposed to H2O2, enabling the binding of Nrf2. On the contrary, in ATRA differentiated cells treated with H2O2, Bach1 displacement was impaired, preventing Nrf2 binding and limiting HO-1 transcription. In conclusion, our findings highlight the central role of Bach1 in HO-1-dependent neuronal response to oxidative stress

Campaña de comunicación integral para combatir la envidia en el Perú

El presente trabajo tiene como objetivo elaborar una campaña de comunicación integral, a solicitud de la Asociación Vale un Perú, para combatir la envidia en el país. A través de la reflexión, acerca de los beneficios del desarrollo conjunto de la sociedad, se busca generar un cambio de actitudes en nuestra audiencia, para conseguir una sociedad más solidaria y así prevenir el desarrollo de la envidia