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The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

The purpose of this study is to investigate the influence of institutional dynamics on road accidents and whether this relationship is moderated by information and communication technology (ICT).

The study adopted a quantitative approach with 133 respondents. Research hypotheses were tested in AMOS version 21. In addition, moderated regression analysis was used to test the moderating role of ICT on the relationship between institutional dynamics and road accidents.

The results show that vehicle maintenance, policy enforcement, safety culture, driver training and driver management positively influence road accidents. Moreover, the study established that ICT moderates the relationship between institutional dynamics and road accidents.

The results of this study serve as a practical guideline for policymakers in the road haulage sector. Managers may gain insights on how to design effective interventions to reduce road accidents.

This research contributes to the existing body of knowledge by exploring previously unexplored moderating paths in the relationship between institutional dynamics and road accidents. By highlighting the moderating role of ICT, the study sheds new light on the institutional dynamics that influence road accidents in the context of road haulage companies.

This research examines what motivates professional truck drivers to engage in eco-driving by linking their self-reports with objective driving scores.

Theory of Planned Behavior (TPB) is illustrated in an embedded, single-case study of a Finnish carrier with 17 of its truck drivers. Data are obtained through in-depth interviews with drivers, their fuel-efficiency scores generated by fleet telematics and a focus group session with the management.

Discrepancies between drivers’ intentions and eco-driving behaviors are illustrated in a two-by-two matrix that classifies drivers into four categories: ideal eco-drivers, wildcards, wannabes and non-eco-drivers. Attitudes, subjective norms and perceived behavioral control are examined for drivers within each category, revealing that drivers’ perceptions did not always align with the reality of their driving.

This study strengthens the utility of TPB through data triangulation while also revealing the theory’s inherent limitations in elucidating the underlying causes of its three antecedents and their impact on the variance in driving behaviors.

Managerial insights are offered to fleet managers and eco-driving solution providers to stipulate the right conditions for drivers to enhance fuel-efficiency outcomes of transport fleets.

This is one of the first studies to give a voice to professional truck drivers about their daily eco-driving practice.

This paper aims to explore whether the key drivers identified in digitalization policies are being prioritized by practitioners in health and social care and to what degree the goals of the policies are being enacted.

The investigation comprised two stages. First, the key drivers of digitalization in the national policies were identified. Second, a survey was disseminated to practitioners within health and social care, asking them to indicate their stance on each key driver (using Likert scales).

The findings of this paper are twofold. First, they demonstrate that practitioners more readily enact the key drivers centered around their everyday operations, such as improving services and care and increasing efficiency. Second, it shows that key drivers of a more rhetorical nature, such as “becoming the best,” do not yield benefits for practitioners.

This paper shows that for policies to have an effect in practice and to contribute to change, they should be rooted in key drivers centered around practitioners’ everyday operations, promoting specificity over abstraction.

While previous studies have involved policy analysis, few studies investigate the enactment of policies, how they are implemented and whether they contribute to changes in practice.

Coopetition is ubiquitous in the economy, but managing effectively this type of relationship between firms remains a challenge for many organizations. This paper investigates the coopetition within corporate groups and focus on factors that determine the simultaneous competition and cooperation between subsidiaries therein.

Drawing on a dataset of 121 corporate groups listed on the Warsaw Stock Exchange (WSE), this paper theoretically advances and empirically validates the impact of 18 factors which determine the coopetition relationship.

This study's findings confirm the importance of an organizational design among external and internal drivers of intrafirm coopetition. However, the role of an environmental uncertainty as a driver of intrafirm coopetition is not proven. Furthermore, the paper finds that internal determinants explain the phenomenon of coopetition between subsidiaries within a corporate group more than determinants related to the environment.

The paper contributes to the coopetition theory by empirical identification of drivers of intrafirm coopetition and advances the corporate groups studies by exploring internal relationships (cooperation and competition) and the determinants therein.

This study aims to develop a comprehensive conceptual framework that serves as a foundation for identifying most critical delay risk drivers for Building Information Modelling (BIM)-based construction projects.

A systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to identify key delay risk drivers in BIM-based construction projects that have significant impact on the performance of delay risk predictive modelling techniques.

The results show that contractor related driver and external related driver are the most important delay driver categories to be considered when developing delay risk predictive models for BIM-based construction projects.

This study contributes to the body of knowledge by filling the gap in lack of a conceptual framework for selecting key delay risk drivers for BIM-based construction projects, which has hampered scientific progress toward development of extremely effective delay risk predictive models for BIM-based construction projects. Furthermore, this study's analyses further confirmed a positive effect of BIM on construction project delay.

The purpose of this paper is to characterize distracted driving by quantifying the response time and response intensity to an emergency stop using the driver’s physiological states.

Field tests with 17 participants were conducted in the connected and automated vehicle test field. All participants were required to prioritize their primary driving tasks while a secondary nondriving task was asked to be executed. Demographic data, vehicle trajectory data and various physiological data were recorded through a biosignalsplux signal data acquisition toolkit, such as electrocardiograph for heart rate, electromyography for muscle strength, electrodermal activity for skin conductance and force-sensing resistor for braking pressure.

This study quantified the psychophysiological responses of the driver who returns to the primary driving task from the secondary nondriving task when an emergency occurs. The results provided a prototype analysis of the time required for making a decision in the context of advanced driver assistance systems or for rebuilding the situational awareness in future automated vehicles when a driver’s take-over maneuver is needed.

The hypothesis is that the secondary task will result in a higher mental workload and a prolonged reaction time. Therefore, the driver states in distracted driving are significantly different than in regular driving, the physiological signal improves measuring the brake response time and distraction levels and brake intensity can be expressed as functions of driver demographics. To the best of the authors’ knowledge, this is the first study using psychophysiological measures to quantify a driver’s response to an emergency stop during distracted driving.

The entrepreneurial ecosystem (EE) literature is dominated by conceptual studies with insufficient theoretical foundations and empirical evidence on the micro-level. This study aims to explore the largely overlooked question of what the drivers that motivate small and medium-sized enterprises (SMEs) to participate in an ecosystem are.

The study adopts a qualitative exploratory approach. The empirical data consists of 19 semi-structured interviews with top management of SMEs in the health tech ecosystem in Finland. The data were analyzed using a thematic content analysis.

This study reveals a typology of drivers that motivate SMEs to participate in an ecosystem. These include social drivers (networking and cooperation and communication and knowledge sharing), resource drivers (access to resources, formal and informal support and market access) and cognitive drivers (shared goals and common values).

The study contributes to the EE research by highlighting the drivers that motivate health tech SMEs to become members of the local ecosystem. It suggests that managers and entrepreneurs need to be aware of the factors related to social, resource and cognitive drivers to ensure the future success of their business.

The study draws evidence from a micro-level perspective which enriches the understanding of the EE phenomenon. It also explores an increasingly relevant but under-researched field, the health tech ecosystem.

Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance.

First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers’ subjective perception was also considered.

The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly.

This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.

One of the distinctive features in Korea and the U.S. trucking industries is the huge difference in the share of owner-operators. While it is around 10~15 percent in the U.S., 80~90% of drivers operate their own truck in Korea. Different from historical explanations of previous researches, this paper deals with this feature theoretically. We examine what brings the difference in asset ownership structures between the Korean and the U.S. trucking industries. Using an analytic framework, we investigate the determinants of truck ownership and the changes in ownership patterns. The model introduces several parameters related to productivities of drivers’ efforts and contractibility to affect drivers’ decision, and values of these parameters in both countries are discussed qualitatively and found to be consistent with the aforementioned characteristics.