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Studies have demonstrated the role of human resource management (HRM) practices and knowledge management processes (KMPs) in innovative performance. However, there is limited focus on the role of HRM practices in facilitating KMPs in organizations, most especially in small and medium enterprises (SMEs) that are constrained by lack of adequate resources, making them dependent on external sources of knowledge. In addressing this gap, this study aims to investigate the link between knowledge-based HRM practices and open innovation (OI) activities through KMPs in Jordanian SMEs.

Following the survey method, 500 manufacturing SMEs in Jordan were randomly selected as participants, with a total of 335 responses collated. The structural equation modeling technique, based on AMOS, was used in analyzing the collected data.

The findings revealed a significant positive relationship between knowledge-based HRM practices and OI. In addition, KMPs was determined to be a significant mediator of the relationship between knowledge -based HRM practices and OI.

The study contributes to the literature by emphasizing the organizational elements that boost OI in SMEs. The findings hold significant implications for enhancing the performance of innovativeness, competitiveness and the socioeconomic advancement in the SMEs sector.

The purpose of this study is to investigate the significance and impact of strategic knowledge management (SKM) practices and organisational change capacity (OCC) in improving strategic thinking and strategic orientation in small and medium-sized enterprises (SMEs) and their contribution in overall improvement of entrepreneurial performance.

Quantitative research methodology using partial least square structural equation modelling with data of 296 sample from the target group as managers and owners from various SMEs in the UK has been used in the study.

The findings suggest that SMEs that invest in SKM and OCC are more proficient at adjusting to fluctuations in the business landscape and develop effective strategies that lead to improved entrepreneurial performance. The study provides evidence that SKM encompasses more than just the acquisition and use of information. It also involves the establishment of a learning and innovation culture that facilitates strategic thinking and direction. Similarly, OCC is not just about implementing change but also about developing the agility and flexibility to adapt to market changes, consumer demands and technology.

According to the research, SMEs may boost their entrepreneurial performance and keep a competitive advantage in the modern, dynamic business environment by investing in SKM and OCC. The capacity of SMEs to implement SKM and organisational change should be encouraged and supported by policymakers and practitioners, who should also offer the necessary tools and assistance to do so.

This study offers a valuable addition to the previously published works on SKM and OCC within SMEs. It offers empirical data that highlights the significance of SKM and OCC in fostering strategic thinking, strategic orientation and ultimately, boosting entrepreneurial performance. The study also highlights the challenges faced by SMEs in implementing SKM and OCC and provides recommendations for overcoming these challenges.

This article aims to unfold digital servitization by exploring the key resources and resource orchestration (i.e. resource configuration and interaction).

This article conducted an explorative two-stage research strategy of Chinese servitized manufacturers using a preliminary case study and fuzzy-set Qualitative Comparative Analysis (fsQCA) design. The data collection was conducted between 2016 and 2021.

This article identifies five key resources – radical, complex technological resources, complementary, specific market resources and digital resources – and their configurations – leveraging market opportunities, leveraging innovation integration and leveraging resource advantages – to facilitate servitization in the digital age. The findings underscore the interaction between technological and market resources as well as the role of digital resources in promoting the servitization journey.

This article contributes to the understanding of servitization in the digital context by examining the key resources and their interactions involved. It builds upon the configurational logic of servitization, expanding the existing framework in the digital context and highlighting the significance of technological and market resource orchestration and interaction in servitization research. Moreover, the paper contributes through its exploratory two-stage approach, going beyond a conceptual understanding of servitization by focusing on both the factors that enable servitization (WHAT) and the configurations that lead to servitization (HOW). Additionally, the article investigates the attributes of resources as lower-level components, addressing the need to explore the micro-level practice of resource realignment. By providing clarity on the configurations of servitization, the paper offers practical guidelines for practitioners on how to effectively utilize resources and benefit from digital servitization.

Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.

In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.

The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.

This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.

The suppliers of experimental resources required in megaprojects are driven by short-term interests, presuming that participation in the digital platform would only increase their inputs and fail to rapidly expand their revenue, resulting in their insufficient motivation to participate. This paper aims to design effective incentives for these suppliers exhibiting the aforementioned behaviour to drive them to participate and actively share their resources on the platform.

This paper develops incentives for applying the digital platform for experimental resource sharing by using a reverse induction approach to model and solve an incomplete information game. It compares the traditional experiment management mode and the new mode of applying the digital platform, taking the degree of sharing experimental resources on the platform as the variable and constructing three incentive models. By analysing these different degrees of sharing and the different experimental and informatisation capabilities of the suppliers, it could obtain the optimal incentive scheme for changes in sharing behaviour.

The results show that the designed incentives could increase the participation of suppliers in the platform and the number of their shared resources and make the benefits of both the supplier and the demand side reach the optimal state of a win-win situation. However, a higher degree of sharing by suppliers does not yield better results. In addition, the incentive coefficients for this degree should be set based on the suppliers’ different experimental and informatisation capabilities and the ratio of input cost-sharing, so as to avoid blind inputs from both supply and demand.

This study fills the research gap regarding incentives of the digital platform of experimental resource-sharing for megaprojects; it contributes to the body of knowledge by providing a quantitative perspective of understanding the experimental resource-sharing behaviour that motivates the usage of the digital platform. Furthermore, it reveals the incentive mechanism for application in different scenarios, and quantitative analysis is conducted to provide practical insights into promoting the new experiment management mode in megaprojects for more effective incentivisation.

Megaproject knowledge innovation (MKI) is perceived as a critical strategy for engineering value co-creation and industrial chain upgrading. Ascertaining the impact mechanism of MKI is a crucial initial step towards improving management practices. Within the framework of complex systems in megaprojects, factors exhibit intricate interdependencies. However, the current domain of knowledge has either overlooked or oversimplified this relationship and therefore cannot propose pragmatic and efficacious strategies for enhancing MKI. To close this gap, this study develops a Bayesian network (BN) model aiming to investigate the interdependencies among MKI-related factors and their impact on MKI.

First, this study implements literature review, expert interview and field investigation to identify the influencing factor nodes for the network model development. Second, a Bayesian network was constructed by integrating the expert knowledge with Dempster-Shafer theory. Next, a MKI measurement model was established using 253 training samples. Finally, the factor significance and optimal MKI improvement strategies are identified from the sensitivity analysis and probabilistic reasoning within the BNs.

The results indicate that (1) the BN model exhibits significant reliability and holds promotion and application value in formulating MKI management strategies; (2) knowledge sharing, shared vision and leadership are the key influencing factors of MKI; and (3) simultaneously improving institutional pressure, leadership and knowledge sharing is the most optimal strategy to enhance MKI.

This study innovatively introduced the BN method into the domain of MKI management, providing an appropriate approach for modelling complex relationships among factors and investigate nonlinear influences. The developed model raises megaproject stakeholders’ awareness about factors influencing MKI and presents quantified strategies that increase the likelihood of maximising MKI levels. Its ease of generalisability positions it as a promising decision support tool, facilitating the implementation of sustainable MKI practices.

In the vibrant world of social commerce (SC), where information flows freely, interactions thrive and online purchases abound, there is an escalating challenge. Users are uninstalling and disengaging due to approach and avoidance stimuli, a trend mirroring the approach-avoidance motivation model (AAMM). Our study, anchored in AAMM and the stimulus-organism-response (SOR) model, aims to dive into the complex dynamics of these factors that shape users' SC continuance intentions.

Our findings, drawn from 472 SC users in Malaysia, paint an intriguing research framework via PLS-SEM analysis by testing the proposed hypotheses. A purposive sampling technique was utilized, deliberately selecting respondents based on specific criteria. Subsequently, data were gathered through the distribution of face-to-face questionnaires at selected shopping malls, facilitating a focused and comprehensive exploration of consumer perspectives.

The empirical results demonstrate the following: (1) Users' determination to stay engaged on SC platforms hinges on approach factors, like emotional support, surveillance gratification and multisensory gratification. (2) Simultaneously, avoidance factors such as technostress and perceived deception exert their negative influence. (3) Flow experience, rooted in flow theory, emerges as the underlying mechanism connecting these duality stimuli, influencing the continuance intention.

In a departure from conventional research, our study pioneers a comprehensive approach and boldly confronts the research gap by introducing a rich tapestry of antecedents, embracing both the appeal of approach factors and the deterrence of avoidance ones, using the AAMM that sheds light on how individuals navigate between embracing opportunities and avoiding pitfalls based on perceived gains and losses. This holistic approach enables us to redefine our understanding of digital engagement dynamics, offering a captivating journey into the realm of user experience and intention that transcends the ordinary.

This paper aims to explore factors influencing suppliers' acceptance, integration challenges, expected benefits and support from customers when implementing a customer-introduced digital supply chain system.

The study investigates the perspective of suppliers using a mixed methodology approach that combines qualitative interviews with a large-scale quantitative survey conducted among 220 internationally located suppliers of an automotive-industrial firm.

As a result, the authors identified 11 factors that drive suppliers' acceptance of customer-introduced digital supply chain systems. These factors have been ranked based on their importance. The top three important factors identified were the digital system being provided at no cost to the suppliers, the system's ability to save time and the system offering benefits to the suppliers.

Further research can be conducted to validate the perspective of suppliers in other industries. Additionally, future studies can investigate the effectiveness of fulfilling these acceptance factors within an actual digital integration setup.

Companies can leverage these insights to accelerate their digital supply chain integration efforts. The insights on acceptance factors, challenges, benefits and support expected by suppliers can serve as a valuable guide for policy and decision makers within the industry.

To the best of the authors’ knowledge, this study is among the first to investigate the perspective of suppliers in the integration of a customer's digital supply chain. By including the supplier's perspective, this study makes a significant contribution to the academic literature about supply chain digitalisation.

Evaluating project success within the construction industry presents challenges due to the unique characteristics of the sector, the complexity of projects, and the involvement of diverse stakeholders. Conducting a bibliometric analysis, this paper aims to unravel the major research themes and methodologies utilised by researchers in studying the critical success criteria for construction projects, as well as extracting these success criteria.

The researchers systematically searched and screened 95 papers from Scopus and Web of Science (WoS) databases. This study conducted research focus parallelship network (RFPN) analysis and keywords co-occurrence network (KCON) analysis using BibExcel and Gephi to cluster the papers, illuminate the relationships among keywords within each cluster, and identify the primary research directions.

Using the RFPN analysis, this study classified the papers into three distinct clusters: infrastructure and public projects success, risk and knowledge management, and contractors and procurement management. Statistical techniques such as structural equation modelling (SEM) and multi-criteria decision-making methods such as analytic hierarchy process (AHP) have been used to analyse project success in the construction industry.

Considering the intensified demand for streamlined digital interactions and the increasing emphasis on sustainability and safety performance, construction companies are recommended to allocate greater investments toward the automation and digitisation of their products and processes. Prioritising modular construction and embracing transformative technologies alongside data science is crucial for enabling well-informed decision-making, and enhancing project success.

This study contributes to the existing body of knowledge by conducting a quantitative and systematic evaluation of the literature on project success criteria in the construction industry and uncovering key research areas. It addresses the pressing need to understand the complexities of construction projects amidst evolving industry dynamics and emerging disruptions. Moreover, by highlighting the implications of digital innovations and modular construction, this study urges deeper exploration into their impact on project performance and stakeholder satisfaction. This research sets a comprehensive framework for investigating the interplay between project complexity, technological advancements, and sustainable practices in the construction sector, paving the way for strategic advancements in the field.