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Previous studies have rarely integrated the financing modes of a capital-constrained manufacturer with the choices of online sales strategies. To address this gap, the authors study how a manufacturer selects optimal financing modes under different sales strategies in three dual-channel supply chains.

This paper considers three sales strategies, namely, combining a traditional retailer channel with one of the direct selling, reselling and agency selling channels, and two common financing modes, namely, bank financing and retailer financing. The authors obtain equilibrium outcomes of the manufacturer and traditional retailer and then provide the conditions for them to select optimal financing modes under three sales strategies.

The results indicate that the manufacturer’s financing decisions rely on the initial capital and interest rates, and the manufacturer selects retailer financing only if the initial capital is relatively larger. In terms of financing mode options, the retailer financing mode is more beneficial for the manufacturer under the three sales strategies. From the perspective of sales strategies, the direct selling model is more beneficial. In addition, the higher the consumer acceptance of the online channel, the more profits the manufacturer obtains.

This paper provides suggestions on how the capital-constrained manufacturer chooses financing modes and sales strategies.

This paper integrates the financing mode and different sales strategies to investigate the manufacturer’s optimal operational decisions. These sales strategies allow us to investigate the manufacturer’s optimal financing modes in the presence of both different financing modes and sales strategies.

Illegitimate tasks are pervasive in organizations, presenting a challenge for employees to mitigate their impact. However, despite their significance, there has been limited research on when and how employees can adapt to these tasks successfully. To address this gap, this study aimed to discover the relationship between illegitimate tasks and adaptive performance, drawing upon the job demands-resources theory. Specifically, this study aimed to examine the moderating role of general self-efficacy and the mediating roles of employee problem-focused and emotion-focused coping.

To examine our hypotheses, we conducted a time-lagged survey, comprising 3 waves and involving 313 employees from twenty enterprises situated in Guangzhou and Sichuan, China. Ordinary least squares (OLS) was adopted to examine our hypotheses.

Our results suggested that general self-efficacy played a crucial role in determining how employees would cope with illegitimate tasks and their subsequent adaptive performance when confronted with illegitimate tasks. Notably, employees who possess high levels of general self-efficacy utilize problem-focused coping, improving adaptive performance in handling illegitimate tasks. Conversely, employees who possess low levels of general self-efficacy rely on emotion-focused coping, leading to lower levels of adaptive performance.

This research contributes to the literature on illegitimate tasks by uncovering when and how such tasks can either promote or hinder adaptive performance. These findings offer practical insights into ways to assist employees in managing illegitimate tasks effectively.

Previous studies have mainly focused on the negative impact of illegitimate tasks on recipients but ignored its impact on observers. Drawing on deservingness theory, this research developed a moderated serial mediation model to examine the underlying mechanism in the relationship between observed illegitimate tasks and observers’ helping behaviour.

This research tested the model using a sample of 218 employees in China through a two-wave field study. A path analysis was conducted with the bootstrapping procedure to test the hypothesized model.

The results showed that the effect of observing illegitimate tasks was contingent upon the degree of the observer’s interpersonal liking towards the recipient. Specifically, when the observer had a high level of interpersonal liking for a coworker, the observer may perceive that the coworker was undeserving of being assigned illegitimate tasks, which increased sympathetic emotion and the sequent helping behaviour.

This study shifted the perspective of the illegitimate task literature from the recipient to the third parties. Additionally, it provided a finer-grained understanding of the mechanism between observed workplace disrespectful treatment and the observer’s helping behaviour.

This study proposes to conceptualize and explicate the progress of end-to-end data pipelines to enable seamless data flow, addressing the mounting demand for instantaneous information in the vibrant field of marketing analytics. Ensuring timely access to inclusive analytics, it empowers marketers to make conversant decisions promptly. The study espouses a conceptual approach, starting with the classification and identification of various data sources crucial for thorough marketing analytics. It probes into the complexities of designing adaptable and scalable architectures for extensive data pipelines, ensuring effective data collection, processing, and storage. Emphasizing case analyses of marketing analytics tools, the study delivers practical insights and exhaustive examinations of existing solutions. The findings offer a broad understanding of the key components and strategies necessary for realizing smooth data flow in real-time marketing analytics. This investigation contributes expressively to the field by outlining a robust framework for continuous data flow, identifying the benefits and challenges associated with data pipelines. From a hands-on standpoint, it provides organizations with appreciated insights for building effective end-to-end data pipelines, bestowing strategies for implementing real-time marketing analytics outlines that enhance decision-making processes. The originality and value of this research lie in its universal approach to addressing the challenges of real-time marketing analytics, offering a fresh viewpoint on creating seamless data flow frameworks. The gathered information has the latent to drive innovation in marketing analytics, serving as a crucial resource for companies aiming to gain a competitive edge in today’s data-driven market. This inclusive approach ensures that the study’s contributions are both theoretically significant and practically applicable.

The advent of digital technologies has ushered in a new era of quality management (QM) known as Quality 4.0 (Q4.0). The successful implementation of Q4.0 requires the involvement of both leaders and employees. Leadership plays a critical role in motivating employees involved in quality practices. However, the mechanisms by which leadership inspires quality professionals to engage in continuous learning and remain vigorous in their roles are not well understood. This study aims to determine the impact of Q4.0 leadership on thriving at work (TAW) among quality professionals and to identify the underlying mechanisms.

Utilising the identity theory and social identity theory, a multilevel TAW model was developed. This study surveyed 63 team leaders and 243 subordinates, who are quality professionals working for companies implementing Q4.0. Multilevel structural equation modelling (MSEM) was applied to assess the hypotheses.

The study finds that Q4.0 leadership enhances TAW among quality professionals. The linkage between Q4.0 leadership and TAW is mediated by work group identification (WGI) at the group level and job identification (JI) at the individual level.

Insights from this study will enable organisations to make informed decisions regarding the leadership styles that best support TAW among quality professionals. By understanding the mechanisms linking Q4.0 leadership to TAW, organisations can foster both WGI and JI, ultimately enhancing engagement and performance in quality initiatives.

This study offers a novel contribution to the QM field by examining the role of Q4.0 leadership in motivating and sustaining the engagement of quality professionals. Exploring the relationships between Q4.0 leadership, WGI, JI and TAW helps to deepen our understanding of how Q4.0 leadership can enhance TAW among quality professionals.

This chapter explores the intersection of cutting-edge algorithms in the financial technology (FinTech) sector, with a particular focus on the application of machine learning (ML) and artificial intelligence (AI) to enhance sustainability and ethical finance practices. The transformative capabilities of ML and AI are examined through their roles in revolutionising financial services by increasing operational efficiency, improving decision-making processes and enhancing risk management strategies. Specific applications discussed include fraud detection, anomaly detection in financial statements, robo-advisory services, prediction of customer deposits, combating money laundering, sentiment analysis, loan eligibility prediction, stock price prediction and the automation of routine tasks through chatbots. Additionally, the chapter addresses the crucial role of AI and ML in supporting green finance initiatives, reducing carbon footprints and promoting financial inclusion, thereby contributing to sustainable economic development. The detailed exploration provides insights into how these advanced technologies are key in shaping the future of the financial industry towards more sustainable outcomes.

Although coworkers’ workplace interpersonal capitalization occurs every day in the workplace, we know little about how it affects employees’ well-being or why and when this impact occurs. To address these questions, we theorized and tested a model that links coworkers’ capitalization to well-being outcomes via perceived relatedness and anxiety and the boundary condition of learning goal orientation.

Time-lagged survey data were collected (N = 304) from a range of organizations in mainland China. Path modeling was used to examine the hypotheses.

The results indicated that coworkers’ capitalization drives an employee to experience either relatedness or anxiety, depending on the employee’s learning goal orientation. Furthermore, responses to relatedness and anxiety trigger autonomous motivation and psychological detachment, respectively.

This study contributes to the capitalization literature by comprehensively explaining the negative and positive effects of coworkers’ capitalization on employees’ well-being.

Due to the growing complexity involved in leveraging the endless possibilities of ICT on all levels, the technical competence of faculties of higher education institutions (HEI) and effective methods for fostering e-readiness has become questionable.

This research has developed and validated an empirically supported e-readiness scale, which can be used by HEIs to assess faculty members’ preparedness toward online teaching. The measurement model and the structural model were developed as the results of exploratory factor analysis and confirmatory factor analysis (n = 245). The previously identified components and their indicators were validated using the structural models and the final scale was developed with five dimensions (“online technological readiness, pedagogical readiness, institutional readiness, learning and delivery readiness and content readiness”).

The faculties’ e-readiness assessment tool, as a useful tool, could aid institutions in identifying problems that affect the implementation of e-learning or digitalization in the institutions and developing strategies in response.

Like any research this research also has some limitations and can be considered as future research probability like the responses for this research were collected from HEI in India; however, a cross-cultural study can be conducted to understand the parameters across the globe. Although the psychometric qualities of the e-readiness scale are acceptable, additional research in various higher educational environments, both nationally and internationally, is required to further establish the scale’s relevance, validation and generalizability.

Although many scales have been developed to assess the readiness level in the education sector, a scale, that holistically measures, the readiness level of faculties from an overall perspective was required. This scale can be used to recognize the e-readiness level of teachers in HEIs. This scale can also help the institutions assess the readiness level of their faculty members and address any improvements required in their teaching and learning pedagogy, further acknowledging training needs.

This paper aims to develop a flexible manufacturing method for multimaterial sand molds to realize efficient additive manufacturing of multimaterial sand molds.

To study the influence of multimaterial sand laying process parameters on the quality of powder bed and optimize the design of multimaterial sand laying device. Numerical simulation and X-ray Computed Tomography are used to study the penetration behavior and curing morphology of resin in different sand particles.

The surface roughness and porosity of the multimaterial powder bed that meet the requirements of sand-based additive manufacturing can be obtained under the optimal printing process, that is, the sanding speed of 140.0 mm/s and sanding roller diameter of 15.0 mm. The resin penetration process of the multimaterial sand molds shows a pattern of transverse expansion and longitudinal penetration. In terms of the resin curing morphology, the maximum thickness of the resin film layer of zircon sand reaches 30.5 ± 1.0 µm, which has the best tensile property, followed by silica sand and the thinnest resin film layer of chromite sand.

In this work, a highly flexible integrated combined sand-laying device suitable for multimaterial sand-laying tests is developed, which can obtain a multimaterial powder bed that meets the needs of sand additive manufacturing. Subsequent casting print tests also verify that the program can meet the needs of multimaterial sand mold additive manufacturing.

This paper aims to investigate the lubrication characteristics of siliconized graphite with a wavy-tilt-dam (WTD) pattern applied to the hydrodynamic face seals.

It focuses on two friction pairs, carbon graphite versus tungsten carbide (CG-TC) and siliconized graphite versus siliconized graphite (SG-SG), through a three-dimensional elastic hydrodynamic lubrication numerical model that integrates finite difference method and finite element method. The consequence of axial elastic deformation of sealing pair materials on film thickness, film pressure, cavitation and sealing performance for a WTD mechanical face seal under full working conditions of ΔP = 0.8, 5.3 and 15.8 MPa are analyzed theoretically.

The nuclear hydrodynamic WTD face seal generates a convergent gap and exhibits a dual-characteristic behavior of hydrodynamic and hydrostatic effects under various ΔP. Compared to the CG-TC, the SG-SG shows a lower minimum film thickness, decreasing by 3.9%, 17.3% and 35.1%. The flow leakage rate decreases by 47.8%, 52.1% and 75.4%. In addition, the film stiffness increases by 46.8%, 49.8% and 97.8%. Thus, the SG-SG better deals with the dynamic tracking problem, and the sealing performance is stable. The strength and hardness of siliconized graphite enhance WTD sealing performance and improve cavitation control in high-pressure applications.

The lubrication characteristics of the siliconized graphite with a WTD pattern could inform the future design of hydrodynamic shallow groove wavy seals in boiler feedwater engineering implements under high-pressure conditions for the nuclear power industry.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0382/