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The purpose of this study, most recent advancements in threedimensional (3D) printing have focused on the fabrication of components. It is typical to use different print settings, such as raster angle, infill and orientation to improve the 3D component qualities while fabricating the sample using a 3D printer. However, the influence of these factors on the characteristics of the 3D parts has not been well explored. Owing to the effect of the different print parameters in fused deposition modeling (FDM) technology, it is necessary to evaluate the strength of the parts manufactured using 3D printing technology.

In this study, the effect of three print parameters − raster angle, build orientation and infill − on the tensile characteristics of 3D-printed components made of three distinct materials − acrylonitrile styrene acrylate (ASA), polycarbonate ABS (PC-ABS) and ULTEM-9085 − was investigated. A variety of test items were created using a commercially accessible 3D printer in various configurations, including raster angle (0°, 45°), (0°, 90°), (45°, −45°), (45°, 90°), infill density (solid, sparse, sparse double dense) and orientation (flat, on-edge).

The outcome shows that variations in tensile strength and force are brought on by the effects of various printing conditions. In all possible combinations of the print settings, ULTEM 9085 material has a higher tensile strength than ASA and PC-ABS materials. ULTEM 9085 material’s on-edge orientation, sparse infill, and raster angle of (0°, −45°) resulted in the greatest overall tensile strength of 73.72 MPa. The highest load-bearing strength of ULTEM material was attained with the same procedure, measuring at 2,932 N. The tensile strength of the materials is higher in the on-edge orientation than in the flat orientation. The tensile strength of all three materials is highest for solid infill with a flat orientation and a raster angle of (45°, −45°). All three materials show higher tensile strength with a raster angle of (45°, −45°) compared to other angles. The sparse double-dense material promotes stronger tensile properties than sparse infill. Thus, the strength of additive components is influenced by the combination of selected print parameters. As a result, these factors interact with one another to produce a high-quality product.

The outcomes of this study can serve as a reference point for researchers, manufacturers and users of 3D-printed polymer material (PC-ABS, ASA, ULTEM 9085) components seeking to optimize FDM printing parameters for tensile strength and/or identify materials suitable for intended tensile characteristics.

Fused Filament Fabrication (FFF) is one of the growing technologies in additive manufacturing, that can be used in a number of applications. In this method, process parameters can be customized and their simultaneous variation has conflicting impacts on various properties of printed parts such as dimensional accuracy (DA) and surface finish. These properties could be improved by optimizing the values of these parameters.

In this paper, four process parameters, namely, print speed, build orientation, raster width, and layer height which are referred to as “input variables” were investigated. The conflicting influence of their simultaneous variations on the DA of printed parts was investigated and predicated. To achieve this goal, a hybrid Genetic Algorithm – Artificial Neural Network (GA-ANN) model, was developed in C#.net, and three geometries, namely, U-shape, cube and cylinder were selected. To investigate the DA of printed parts, samples were printed with a central through hole. Design of Experiments (DoE), specifically the Rotational Central Composite Design method was adopted to establish the number of parts to be printed (30 for each selected geometry) and also the value of each input process parameter. The dimensions of printed parts were accurately measured by a shadowgraph and were used as an input data set for the training phase of the developed ANN to predict the behavior of process parameters. Then the predicted values were used as input to the Desirability Function tool which resulted in a mathematical model that optimizes the input process variables for selected geometries. The mean square error of 0.0528 was achieved, which is indicative of the accuracy of the developed model.

The results showed that print speed is the most dominant input variable compared to others, and by increasing its value, considerable variations resulted in DA. The inaccuracy increased, especially with parts of circular cross section. In addition, if there is no need to print parts in vertical position, the build orientation should be set at 0° to achieve the highest DA. Finally, optimized values of raster width and layer height improved the DA especially when the print speed was set at a high value.

By using ANN, it is possible to investigate the impact of simultaneous variations of FFF machines’ input process parameters on the DA of printed parts. By their optimization, parts of highly accurate dimensions could be printed. These findings will be of significant value to those industries that need to produce parts of high DA on FFF machines.

The purpose of this research is to examine the narratives of victims of abusive supervision. We explore the meaning or “lessons” victims derive from those experiences and how they shape the victims’ views of self, work and organization in relation to navigating their subsequent jobs.

We analyzed how appraisals of supervisory abuse transform victims’ narratives and their consequent work attitudes through sensemaking processes. Semi-structured interviews with the past victims of abusive supervision generated a four-stage model of how sensemaking shapes victims’ future work attitudes. Our interpretations were guided through narrative thematic analysis based on the constructionist approach.

Victims’ lessons learned are predominantly framed by their retrospective post-event appraisal of abuse (based on its severity) once individuals are no longer subject to abusive supervision. With greater distance from the abuse, victims can process the abuse and better understand the motivation of the abuser, enabling the process of causal attributions. These attributions further shape victims’ narratives and future work attitudes through a complex interplay of retrospective and prospective sensemaking mechanisms. The victims broadly reported proactive (with higher self-awareness and endurance) and reactive (self-protection, and emotional scars) lessons. A four-stage model was proposed based on our findings.

Abusive supervision remains a persistent issue experienced by many individuals at some point in their working life. However, little is known about how victims make sense of the event post-abuse and how this sense-making guides their future work behaviors. Understanding this phenomenon provides insight into how employees navigate through adversity and construct a more positive future. The contribution of this narrative inquiry is threefold. First, it explores how individual appraisals of supervisory abuse frame their (1) mechanisms of narrative construction; and (2) future work attitudes. Second, our findings demonstrate how narrative construction is a fluid process often informed by the process of retrospective and prospective sensemaking. Finally, our research suggests two broader categories of lessons that victims internalize and carry forward to their subsequent jobs.

The purpose of this paper is to fill a gap in the literature regarding the open innovation management approaches that small and medium-sized enterprises (SMEs) can use to access digital technologies and incorporate them into their organizational processes. The research question is: What organizational and process-level managerial actions do SMEs take to successfully access and implement digital technologies within their organizational processes?

Using Guertler et al.'s (2020) Action Innovation Management Research (AIM-R) framework, this study examines the digital transformation experiences of 10 European SMEs to gain insights into the managerial actions that foster successful digital transformation.

The findings of the paper reveal two major contributions. First, a digital transformation roadmap for SMEs is proposed, with a focus on accessing external resources and reconfiguring internal ones to ease their digital transformation journey. Second, three distinct paradoxes that influence the digital transformation process in SMEs are highlighted, providing useful insights into the challenges and tensions SMEs face during this journey.

This paper provides a unique perspective on the digital transformation of SMEs by examining the managerial actions required for successful technology adoption and revealing the paradoxes that may emerge during this transformative process. The findings form the basis for future research, deepening our understanding of digital transformation in SMEs and providing actionable advice to managers and practitioners navigating this journey.

Drawing on the conservation of resources (COR) theory, this study aims to examine the effects of servant leadership and despotic leadership on employees’ happiness at work (HAW) through job crafting.

To test the hypothesized relationships, the data were collected from 309 Pakistani employees. Structural equation modeling was used to analyze the data.

The findings showed that servant leadership is an optimal leadership style for creating employees’ HAW. In addition, job crafting was found to mediate the effects of servant leadership on employees’ broad-based positive attitudinal outcome (HAW). Moreover, results showed that despotic leadership negatively influences employees’ HAW through job crafting.

This study is novel as it investigates how newer forms of positive (servant) and negative (despotic) leadership styles influence employees’ multidimensional attitudinal outcome (HAW) via job crafting. By doing so, this research extends the nomological network of servant leadership, despotic leadership, job crafting and HAW.

While Digitalisation is gaining momentum among practitioners and the scientific world, there is still a struggle to embark on the digitalisation journey successfully. The struggles are more significant for SMEs compared to large companies. Such transformation could face internal resistance, which evokes the need to put it into a socio-technical perspective such as lean. This paper investigates how SMEs could implement digital tools and technologies in their operations.

We relied on a multiple case study design in three SME manufacturing companies in Italy. Based on the experience of those companies, the struggles in the implementation and the lessons learned, we formulate an implementation model of digital tools driven by lean thinking.

Companies tend to implement first digital tools that help with real-time data collection and stress that introducing digital tools becomes challenging without reducing waste in production. The model stresses top management commitment, middle-line involvement and operator training to resist change. All these factors coincide with socio-technical lean bundles developed by seminal works. In addition, the study highlights that financial incentives are not necessarily the common barrier to digital tools implementation in SMEs but rather the cultural aspect.

Our paper enriches the extant body of knowledge by deriving knowledge around digitalisation implementation through lessons learned and corrective actions. It allows managers to benchmark and compare the current state of the implementation process with that of other companies and the one proposed to make corrective actions when necessary.

Research on leaders’ knowledge management systems focuses exclusively on how leaders gather and disseminate knowledge in collaboration with external actors. Not much is known about how leaders address the psychological aspects of employees and strategize internal communication. In addition, while previous work has treated high uncertainty as a default feature of crisis, this study aims to propose that perceived uncertainty varies in experience/meaning and has a crucial bearing on the relative balance of cognitive/emotional load on the leader and behavioral/psychological responses.

The authors contribute by qualitatively examining the role of leader knowledge systems in designing communication strategies in the context of the COVID-19 crisis by investigating communication characteristics, style, modes and the relatively unaddressed role of compassion/persuasion. In this pursuit, the authors interviewed 21 C-suite leaders, including chief executive officers, chief marketing officers, chief financial officers, chief human resource officers and founders, and analyzed their data using open, axial and selective coding, which were later extracted for representative themes and overarching dimensions.

Drawing from grounded theory research, the authors present a framework of knowledge systems and their resultant communication with employees in high uncertain and low uncertain crises. The authors highlight interactions of a set of concepts – leaders’ preparedness, leaders’ support to employees tailored communication adapted to perceived uncertainty, leading to enhanced trust – in the achievement of outcomes related to balancing operational and relational systems with employees. The findings suggest that a structured process of communication helps employees mitigate any concern related to uncertainty and feel confident in their leadership.

The research has implications for leaders in managing their knowledge systems, for human esources practitioners in designing effective internal communication programs, as well as for scholars in knowledge management, communication and leadership.

Drawing on conservation of resources theory, this study aims to examine how employees’ experiences of excessive workloads may direct them away from efforts to share knowledge with other organizational members, as well as the circumstances in which this process is more or less likely. To untangle the process, the authors predict a mediating role of job dissatisfaction and moderating roles of two complementary resources that help employees cope with failure: resilience as a personal resource and organizational forgiveness as an organizational resource.

Survey data were gathered from employees of an organization that operates in the construction retail sector. The Process macro provides an empirical test of the moderated mediation dynamic that underpins the proposed conceptual framework.

The statistical findings affirm that an important channel through which employees’ perceptions that their work demands are unreasonable escalate into a diminished propensity to share knowledge is their lack of enthusiasm about their jobs. Their ability to recover from challenging work situations and their beliefs that the organization does not hold grudges against people who commit mistakes both mitigate this harmful effect.

For organizational practitioners, this research shows that when employees feel frustrated about extreme work pressures, the resource-draining situation may escalate into diminished knowledge sharing, which might inadvertently undermine their ability to receive valuable feedback for dealing with the challenges. From a positive perspective, individual resilience and organizational forgiveness represent resources that can protect employees against this negative spiral.

This study explicates an unexplored harmful effect of strenuous workloads on knowledge sharing, which is explained by employees’ beliefs that their organization fails to provide satisfactory job experiences. This effect also is mitigated to the extent that employees can draw from valuable personal and organizational resources.

A novel type of heat transfer fluid known as hybrid nanofluids is used to improve the efficiency of heat exchangers. It is observed from literature evidence that hybrid nanofluids outperform single nanofluids in terms of thermal performance. This study aims to address the stagnation point flow induced by Williamson hybrid nanofluids across a vertical plate. This fluid is drenched under the influence of mixed convection in a Darcy–Forchheimer porous medium with heat source/sink and entropy generation.

By applying the proper similarity transformation, the partial differential equations that represent the leading model of the flow problem are reduced to ordinary differential equations. For the boundary value problem of the fourth-order code (bvp4c), a built-in MATLAB finite difference code is used to tackle the flow problem and carry out the dual numerical solutions.

The shear stress decreases, but the rate of heat transfer increases because of their greater influence on the permeability parameter and Weissenberg number for both solutions. The ability of hybrid nanofluids to strengthen heat transfer with the incorporation of a porous medium is demonstrated in this study.

The findings may be highly beneficial in raising the energy efficiency of thermal systems.

The originality of the research lies in the investigation of the Darcy–Forchheimer stagnation point flow of a Williamson hybrid nanofluid across a vertical plate, considering buoyancy forces, which introduces another layer of complexity to the flow problem. This aspect has not been extensively studied before. The results are verified and offer a very favorable balance with the acknowledged papers.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.