bluuebunny/crossref_metadata_2025_split huggingface dataset:
Organizational capabilities for digital innovation: a systematic literature review
Authors: Motamedimoghadam Mohsen , Mira da Silva Miguel , Amaral Miguel 
Published: December 2024

PurposeThe rapid advancement of digital technologies compels companies across all industries to develop new capabilities to foster innovation and sustain competitiveness. Consequently, scholarly debates have intensified regarding how these new capabilities contribute to companies’ innovation endeavors. This study addresses this imperative by exploring two primary research questions: first, identifying the essential organizational capabilities for digital innovation; and second, examining how these capabilities facilitate innovation. The objective is to develop a comprehensive conceptual framework that classifies digital innovation capability as a higher-order organizational capacity, offering valuable insights for both academic scholarship and practical applications in digital innovation management.Design/methodology/approachUsing a qualitative approach, this study combines a systematic literature review with grounded theory principles to analyze 38 empirical papers from Scopus and Web of Science databases. The rigorous multi-stage coding process – open, axial and selective coding – facilitated the identification and synthesis of valuable insights for digital innovation capabilities. This approach ensures a comprehensive yet focused review, supporting the development of a robust theoretical framework.FindingsFour critical capability clusters were identified to shape digital innovation capabilities: sensing, analytic-driven, digital platform and orchestration. Sensing capabilities enhance environmental awareness and enable organizations to detect market needs and opportunities, fostering customer-centric innovations. Analytic-driven capabilities leverage data for insightful decision-making and trend analysis. Digital platform capabilities highlight the strategic use of technological infrastructures to enable collaborative innovation, integrating diverse capabilities and objectives. Orchestration capabilities focus on effective coordination of resources and partnerships, ensuring sustained digital innovation by bridging capability gaps and reconfiguring resources. Collectively, these clusters offer a holistic framework for excelling in the dynamic digital innovation landscape.Originality/valueWhile previous literature has focused on the impact of individual capabilities on digital innovation, this study offers a novel and integrative framework that categorizes digital innovation capabilities into four distinct yet interconnected clusters: sensing, analytic-driven, digital platforms and orchestration. This framework delineates the unique roles each capability plays in the digital innovation process. By synthesizing empirical studies and constructing a robust theoretical framework, this research significantly contributes to both academic scholarship and practical applications, offering essential strategies for organizations to enhance their digital innovation efforts through sustainable capability development.
Assessing the influence of supply chain collaboration on the performance of manufacturing SMEs in Rwanda
Authors: Uwamahoro Alexis , Nadeem Simon Peter , Shale Ismail Noor , Wachiuri Elizabeth 
Published: December 2024

PurposeThis research examines how supply chain collaboration, underpinned by stakeholder trust, information sharing and strategic partnerships, impacts the performance of manufacturing SMEs in Rwanda. The focus on manufacturing SMEs is due to their vital role in the economy and their distinctive resource dynamics.FindingsThe study demonstrates that supply chain collaboration, particularly through strategic partnerships and stakeholder trust, positively impacts supply chain performance. While information sharing’s influence is currently limited by technological constraints, the findings highlight the need for a comprehensive approach to address existing challenges and emphasise the crucial roles of stakeholders and policymakers in supporting SMEs’ performance.Research limitations/implicationsThis research contributes to a broader understanding of supply chain collaboration, its impact on performance, its interactions with other organisational factors and its implications for managerial decision-making, academic research and supply chain partnerships.Originality/valueThis research is one of the few to demonstrate the impact of supply chain collaboration on the performance of manufacturing SMEs in developing countries, particularly Rwanda.
How does ethical leadership enhance employees’ innovative behavior? The roles of work group cohesiveness and openness to experience
Authors: Tran Pham Toan Khanh 
Published: December 2024

Purpose
The purpose of this study is to investigate how ethical leadership impacts employees’ innovative work behavior among public employees through the mediating role of group cohesiveness. This work further offers deeper insight into the moderating mechanism of openness to experience in the relationship between ethical leadership and employees’ innovative work behavior.

Design/methodology/approach
Three time-lagged sets of data (n = 532) were collected among Vietnamese public employees. The partial least squares – structural equation modeling method was applied to test the research hypotheses.

Findings
Ethical leadership positively relates to employees’ innovative work behavior. Furthermore, group cohesiveness plays a mediating role in the link between ethical leadership and employees’ innovative work behavior. The moderating impact of openness to experience between ethical leadership and employees’ innovative work behavior is supported.

Originality/value
This inquiry is probably the first attempt to explore the mechanism linking ethical leadership and employees’ innovative work behavior through the mediator of group cohesiveness. Additionally, this study extends the current knowledge by investigating the moderating role of openness to experience in ethical leadership and employees’ innovative work behavior nexus.
Communication and job satisfaction among public employees: evidence from large-scale surveys with healthcare professionals
Authors: Pirrotta Luca , Ferrari Amerigo , Cantarelli Paola , Belle Nicola 
Published: December 2024

PurposeCommunication and job satisfaction are two key factors for the success of public organisations. The study aims, firstly, to examine the effects of training activities and internal meetings on the perceived quality of communication processes; secondly, to explore the nuanced relationship between communication and job satisfaction.Design/methodology/approachThis is a cross-sectional study based on results from organisational climate surveys conducted between 2019 and 2020 in six Italian Regional Healthcare Systems, involving a total of 58,888 employees. Linear regression models were performed.FindingsResults highlight that employee satisfaction is positively influenced by high-quality internal communication. The organisation of frequent internal meetings and the offer of ad hoc training sessions on communication were found to be antecedents of good communication.Practical implicationsThe study offers practical implications for healthcare organisations, highlighting specific strategies that can be employed to enhance internal communication and, subsequently, job satisfaction. The emphasis on training programmes and internal meetings provides actionable insights for organisational improvement.Originality/valueThe originality and value of this study lie in its unique large datasets, which significantly strengthen the reliability of the findings and make them more applicable to a wider range of contexts. Also, the exploration of the relationship between internal communication processes and job satisfaction within public healthcare organisations contributes to the growing body of knowledge in organisational studies.
Instance segmentation of on-line wear debris using deep convolutional neural network with transfer learning
Authors: Li Jingming , Chen Mingzhi 
Published: December 2024

Purpose
This study aims to apply deep convolutional neural network Mask-R-CNN algorithm based on transfer learning to realize the segmentation of online wear fragments.

Design/methodology/approach
Wear debris analysis is considered to be one of the most effective methods to maintain the condition of mechanical equipment. In this paper, the friction and wear testing machine was used to design pin-disk rotation, pin-disk reciprocation and four-ball test to produce cutting, sliding, laminar and fatigue debris. A semi-online sampling system was designed to collect ferrographic images containing various fragments. The images were rotated and flipped to augment the data and enhance the generalization ability of the model. The data set required for data analysis is established. Using COCO pre-trained Mask R-CNN data set as a benchmark, the region proposal network (RPN) is trained with labeled wear debris images to enhance the ability of RPN to recognize background and wear debris. Two transfer learning scenarios are tested in the network head of the Mask R-CNN.

Findings
The results show that the deep convolutional neural network is suitable for the automatic classification and detection of wear fragments. Through transfer learning and proper training configuration, the ferrographic image recognition based on Mask R-CNN achieves high accuracy.

Originality/value
The results show that the deep convolutional neural network is suitable for the automatic classification and detection of wear fragments. Through transfer learning and proper training configuration, the ferrographic image recognition based on Mask R-CNN achieves high accuracy.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0182/
A design thinking approach to integrate supply chain networks for circular supply chain strategy in Industry 4.0
Authors: Lin Kuo-Yi , Chu I-Tien 
Published: December 2024

PurposeEmbracing circular economy principles in integrating supply chain networks is pivotal for firms navigating the complex terrain of Industry 4.0, as it addresses the urgent need for sustainable competitive advantage in the rapidly evolving service design landscape. Moreover, promoting responsible consumption and production practices within these networks ensures the efficient use of resources, minimizing waste and environmental impact while fostering long-term sustainability.Design/methodology/approachThis study emphasizes the integration of design thinking principles as a strategic response to the challenges posed by emerging design systems in Industry 4.0, with a focus on effectively meeting user requirements and managing competitive pressures within circular supply chain strategies.FindingsAn empirical study validates the impact of the ROCKET model, utilizing data mining to uncover the underlying patterns of thought and action among participants, thereby providing insights into facilitating a circular supply chain strategy. The findings present a robust framework and identify key motivational factors from a project management perspective, specifically tailored for young innovators. The study underscores the importance of effectively integrating supply chain networks, not only to enhance collaborative experiences but also to empower innovators to develop operational protocols aligned with the ROCKET model, thus advancing the circular economy agenda within the Industry 4.0 landscape.Originality/valueLeveraging design thinking, widely recognized for its versatility and pivotal role in fostering innovation, this research investigates the cognitive frameworks and mindsets that drive the innovation journey and its outcomes. Despite its potential, a noticeable gap between experienced design professionals and novices can result in prolonged R&D timelines, quality control issues and resource allocation challenges, which impede effective supply chain integration. To address this gap, the study introduces the ROCKET model, inspired by motivational strategies to support innovation management, with a particular emphasis on integrating supply chain networks to promote a circular economy within the Industry 4.0 context.
Gender diversity on boards and earnings forecast accuracy: insights from India
Authors: Reddy Sudheer , Jadhav Aditya Mohan , Prasad Krishna 
Published: December 2024

PurposeThis paper explores the relationship between gender diversity on corporate boards and the accuracy of analysts’ earnings forecasts. The study focuses on gender-diverse boards as effective monitors, which are expected to influence corporate disclosures, reducing information asymmetry positively and improving forecast accuracy. The unique context of India’s gender quota policy on corporate boards and its relatively weak corporate governance structure offers an ideal setting to investigate this relationship.Design/methodology/approachThe study utilises the generalised method of moments dynamic panel regression to address this research objective, analysing data from 217 Indian firms listed on the National Stock Exchange from 2014 to 2019.FindingsThe findings reveal that greater gender diversity on corporate boards positively impacts forecast accuracy. Specifically, having more women directors on the board enhances forecast accuracy, with a critical mass of women directors (more than one woman) further amplifying this effect. The study also shows that independent women directors significantly improve forecast accuracy, whereas grey women directors (those with family connections or non-independent roles) negatively affect it.Originality/valueThis study contributes significantly in two key aspects. Firstly, it sheds light on the value of women directors on boards in a country where women’s representation is mandated. Secondly, the research highlights the crucial role of independent women directors in ensuring robust financial oversight, particularly in an emerging economy.
How NFTs contribute to consumers’ purchase intention towards luxury fashion physical products
Authors: Zhang Liufang , Phang Ing Grace 
Published: December 2024

PurposeThis study aims to examine the impact of non-fungible tokens (NFTs’) characteristics on Chinese consumers’ purchase intention towards luxury fashion physical products. It also investigates the mediating role of perceived hedonic value and moderating role of perceived NFT–physical product fit during the buying process.Design/methodology/approachA conceptual model combining Stimuli–Organism–Response Model and Theory of Consumption Value was established. A purposive sampling method was adopted to collect data from luxury fashion consumers aged 21–41 who lived in four Tier 1 cities in China. Structural equation modelling and SmartPLS 4.0 were utilized to analyse the 304 valid questionnaires collected.FindingsThe study’s findings indicate that luxury fashion NFTs with four characteristics (NFT scarcity, NFT exclusivity, NFT design aesthetic and NFT novelty) affect Chinese consumers’ purchase intention towards luxury fashion physical products positively, with perceived hedonic value mediating these relationships. Further, perceived NFT–physical product fit moderates the relationship between perceived hedonic value and purchase intention.Originality/valueThis study bridges a gap in investigating the interplay between NFTs as intangible collectibles and tangible products, by stressing the significant role played by NFTs in influencing the purchase intention of luxury fashion products. This paper contributes to an understanding of consumers’ psychological responses and behaviours towards NFTs, providing a new perspective in the study of luxury fashion NFTs in the context of marketing strategy and consumption.
Crafting food destination image in the social media age: dynamics of consumption, experience and culture differences
Authors: Ibrahim Muhamad Aizuddin , Wan Mohd Zain Wan Mohd Adzim , Mior Shariffuddin Nur Shahirah , Azinuddin Muaz , Mohd Salim Muhammad Nur Hidayat , Zainul Nur Hanifa 
Published: December 2024

PurposeThis study investigates how tourists’ local food consumption value, local food experiential value and food culture differences influence food destination image, with food destination attractiveness acting as the mediator. The moderating role of social media influencers is also analysed within this interrelationship.Design/methodology/approachThis study employed a quantitative research design and purposive sampling to collect data. Partial least square-structural equation modelling (PLS-SEM) was employed to test the research hypotheses, with 312 food tourists participating.FindingsThe results indicate that tourists’ local food consumption value, tourists’ local food experiential value and tourists’ food culture differences positively influence food destination attractiveness, which, in turn, mediates their impact on food destination image. However, the moderating role of social media influencers has a significant but negative effect on the relationship between food destination attractiveness and food destination image.Practical implicationsThe research findings indicate that, by considering factors such as overall consumption experiences, cultural differences and social media management, destination stakeholders can capitalise on local food to enhance destination attractiveness and image significantly.Originality/valueThis study provides new insights into the significance of food consumption experiences and their values in tourism while highlighting the critical role of local food culture differences in enhancing each destination’s attractiveness and image. Additionally, it emphasises the subtle influence of social media influencers in promoting destinations, particularly within the context of food tourism.
Organizational learning amidst a crisis: lessons from the biopharmaceutical sector during COVID-19
Authors: Tuazon Gerson , Sun John Peikang , Bhardwaj Varun , Wolfgramm Rachel 
Published: December 2024

PurposeThe purpose of the research is to investigate the impact of affective and emotional experiences on organizational learning in highly dynamic and chaotic environments, specifically in the context of the COVID-19 crisis.Design/methodology/approachBased on an intensive 12-month inductive study, 24-project managers and 16 team members from biopharmaceutical organizations were interviewed and a thematic analysis was conducted.FindingsThree themes emerged from the findings: (1) developing affective maturity as a socio-emotional resource, (2) mixed-motive emotional dynamics and (3) meaning-oriented organizational identification and commitment. The context of the COVID-19 crisis provided an unconventional performance environment.Research limitations/implicationsOur study has several limitations, offering avenues for future research. Firstly, our focus on biopharmaceutical organizations, with their unique socio-cultural influences and management styles, may limit the generalizability of our findings to other sectors and institutional contexts. However, regulatory mechanisms in this sector may align with knowledge-based sectors, emphasizing the influence of organizational values and best practices. Secondly, our reliance on a posteriori interview data limits real-time observation of organizational learning (OL) processes. Future research could employ diverse data sources and survey methods for corroboration. Additionally, cross-cultural studies might explore how different societies respond to crises. Multi-level perspectives could also enhance understanding of affective experiences and their impact on OL outcomes.Originality/valueThe study contributes new insights into OL through its focus on how affective experiences and affective organizing efforts shape OL. We offer a novel and emergent theoretical model of OL in the context of trauma which has implications for organizations particularly in the areas of information processing and decision-making.
Evaluation of novel 3D printed foam patterns for rapid investment casting based on fused filament fabrication
Authors: Fedorov Konstantin , Ravindran Comondore , Fayazbakhsh Kazem 
Published: December 2024

Purpose
This study aims to evaluate the effectiveness of three-dimensional (3D) printed foam polylactic acid (PLA) patterns in reducing ceramic shell stresses and cracking during burnout in the rapid investment casting (RIC) process to improve casting yield and dimensional tolerances.

Design/methodology/approach
Cylindrical and step-wedge patterns were 3D printed using foam PLA feedstock and compared with patterns from plain PLA and Polyvinyl Butyral (PVB). The patterns were shelled using ceramic slurry and investment cast in A356.1 aluminum alloy. Shell cracking and dimensional tolerances of resulting castings were assessed. Additionally, a complex component was 3D printed, laser-scanned, then cast and rescanned to evaluate dimensional accuracy. Finite Element Analysis (FEA) was conducted on cylindrical geometries to analyze internal mold pressure because of thermal stresses during burnout.

Findings
The foam PLA for all patterns produced no shell cracking during both ramp and flash burnouts. Castings made from foam PLA patterns showed improved dimensional tolerances and a narrower error distribution in GD&T analysis compared to those made from PLA and PVB. FEA results indicated that the thermomechanical properties of foam PLA reduce internal mold pressure by over 90%, which decreased internal shell stresses.

Originality/value
This research introduces a novel application of 3D printed foam PLA feedstock in the RIC process as a pattern material. This study demonstrates that foam PLA patterns effectively eliminate shell cracking during burnout and enhance dimensional accuracy. The findings of this study offer a new approach for improving dimensional tolerances and casting yield in RIC, which has not been previously explored.
Structural dimensions and scale development of research motivation among master’s students in the humanities and social sciences
Authors: Ren Xiaobin 
Published: December 2024

Purpose
This study aims to delve into the multidimensional structure of research motivation among master’s students in the humanities and social sciences and to develop an accurate tool for measuring their motivational levels.

Design/methodology/approach
This study used semistructured in-depth interviews with 21 master’s students from the humanities and social sciences. Grounded theory analysis was used to identify key dimensions of research motivation. An initial questionnaire with 24 items was developed based on the findings, which was then revised by experts and master’s students. The modified questionnaire was validated among 283 master’s students in Chinese universities. Further validation was conducted with 319 samples to assess reliability and model fit.

Findings
This study identified five key dimensions of research motivation: subjective norms, self-realization, emotional interest, social interaction and cognitive value. These dimensions were used to construct a research motivation model. The final validated questionnaire, containing 21 items, demonstrated good reliability and model fit, making it a robust tool for assessing research motivation in this specific group.

Originality/value
This study contributes to developing a tailored measurement tool of research motivation specifically for master’s students in the humanities and social sciences. It provides valuable insights for graduate education stakeholders, including educators, advisors and graduate management departments, by offering a deeper understanding of the motivational factors driving students’ research engagement and academic development.