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This study aims to investigate the direct effect of intellectual capital on the organizational performance of Indonesian state-owned enterprises (SOEs) and their subsidiaries. Furthermore, it also examines whether the relationship is mediated by open innovation and moderated by organizational inertia.

This study is designed as quantitative research. A survey method is employed to collect data by distributing questionnaires to the upper-level managers of the SOEs and their subsidiaries. A total of 293 questionnaires were distributed to the respondents, and 97 responses were obtained for further analysis. The partial least square structural equation modeling (PLS-SEM) is used to test the hypotheses. A mediation-moderation research framework is employed.

The results show that intellectual capital has a positive effect on organizational performance. Further results also demonstrate that open innovation mediates the intellectual capital–organizational performance relationship and organizational inertia moderates the intellectual capital–organizational performance relationship. Theoretically, the findings contribute to the resource-based view (RBV) and knowledge-based view (KBV) by providing empirical evidence of the importance of distinctive internal resources in achieving superior organizational performance. Practically, the findings provide strategic information for managers that they should properly manage intellectual capital, open innovation and organizational inertia because of their effects on organizational performance.

First, this study addresses the previous research gaps by confirming that intellectual capital has a positive effect on organizational performance in the research setting of an emerging market. Second, by using a mediation research framework, this study shows that open innovation mediates the relationship between intellectual capital and organizational performance. Third, by using a moderating research framework, this study also reveals that organizational inertia weakens the relationship between intellectual capital and organizational performance. Those associations are rarely researched.

The adoption of mobile payment remains low in certain regions, highlighting the need to identify the factors that enable and inhibit its adoption. This study aims to address this gap by investigating the role of information security, loss aversion and the moderating influence of the herd effect on Inertia and behavioral intentions in the adoption of mobile payment systems.

A structural equation model was developed and tested with 332 valid questionnaires to examine the proposed hypotheses.

The empirical results reveal that information security plays a significant role as an enabler, while loss aversion acts as an inhibitor of mobile payment adoption. Furthermore, the study uncovers the moderating influence of the herd effect on the relationship between Inertia and behavioral intentions.

This study was conducted in a specific region and may not be generalizable to other regions. Future studies could expand the sample size and scope to enhance the external validity of the findings.

This study offers practical implications for mobile payment service providers. Understanding the key enabling and inhibiting factors identified in this study can guide providers in designing and improving their services. Strengthening information security measures can help build trust among potential adopters, while offering incentives can mitigate the impact of loss aversion and encourage early adoption.

The findings of this study have social implications as they contribute to promoting the adoption of mobile payment systems. Increased adoption can enhance financial inclusion and stimulate economic development.

This study provides novel insights into the enabling and inhibiting factors of mobile payment adoption and highlights the moderating role of the herd effect. By shedding light on the influence of social norms on individual behavior in the context of mobile payment adoption, this study contributes to the existing literature and advances our understanding of this phenomenon.

Amidst compounding crises and increasing global population’s nutritional needs, food supply chains are called to address the “diet–environment–health” trilemma in a sustainable and resilient manner. However, food system stakeholders are reluctant to act upon established protein sources such as meat to avoid potential public and industry-driven repercussions. To this effect, this study aims to understand the meat supply chain (SC) through systems thinking and propose innovative interventions to break this “cycle of inertia”.

This research uses an interdisciplinary approach to investigate the meat supply network system. Data was gathered through a critical literature synthesis, domain-expert interviews and a focus group engagement to understand the system’s underlying structure and inspire innovative interventions for sustainability.

The analysis revealed that six main sub-systems dictate the “cycle of inertia” in the meat food SC system, namely: (i) cultural, (ii) social, (iii) institutional, (iv) economic, (v) value chain and (vi) environmental. The Internet of Things and innovative strategies help promote sustainability and resilience across all the sub-systems.

The study findings demystify the structure of the meat food SC system and unveil the root causes of the “cycle of inertia” to suggest pertinent, innovative intervention strategies.

This research contributes to the SC management field by capitalising on interdisciplinary scientific evidence to address a food system challenge with significant socioeconomic and environmental implications.

Supply chain resilience and knowledge management (KM) processes have received increasing attention from researchers and practitioners. Nevertheless, previous studies often treat the two streams of literature independently. Drawing on the knowledge-based theory, this study aims to reconcile these two different streams of literature and examine how and when KM processes influence supply chain resilience.

This research develops a conceptual model to test a sample of data from 203 Chinese manufacturing firms using a structural equation modeling method. Specifically, the current study empirically examines how KM processes affect different forms of supply chain resilience (supply chain readiness, responsiveness and recovery) and examines the moderating effect of blockchain technology adaptation and organizational inertia on the relationship between KM processes and supply chain resilience.

The findings show that KM processes positively affect three dimensions of supply chain resilience, i.e., supply chain readiness, responsiveness and recovery. Besides, the study reveals that blockchain technology adoption positively moderates the relationships between KM processes and supply chain resilience, whereas organizational inertia negatively moderates these above relationships.

This research linked the two research areas of supply chain resilience and KM processes, further bridging the gap in the research exploration of KM in the supply chain field. Next, this study contributes to supply chain resilience research by investigating how KM systems positively impact supply chain readiness, responsiveness and recovery. In addition, this study found a moderating effect of blockchain technology adaption and organizational inertia on the relationship between KM processes and supply chain resilience. These findings provide a reference for Chinese manufacturing firms to strengthen supply chain resilience, achieve secure supply chain operations and gain a competitive advantage in the supply chain. This studys’findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

The purpose of this paper is to examine the resistance behavior of smart factories in small and medium-sized enterprises (SMEs). Drawing upon dual factor perspective, this study examines how two types of quality and perceived usefulness impact user resistance as enabling factors and how switching cost, skepticism, habit and inertia contribute to user resistance as inhibiting factors. Additionally, multi-group analysis is employed to compare small and medium enterprises.

Purposive sampling technique was employed to collect 460 Korean SMEs employees, consisting of 235 small enterprises and 225 medium enterprises. Partial least squares structural equation modeling was used for data analysis.

The results reveal that all three inhibiting factors, switching cost, skepticism and habit, are key antecedents of inertia. In small enterprises, skepticism has a greater impact on inertia, which in turn strongly affects resistance. Additionally, system quality is more crucial for small enterprises, whereas information quality holds more importance for medium enterprises in mitigating resistance. Moreover, when the implementation level of a smart factory is high, the effect of perceived usefulness on user resistance diminishes.

This study has revealed the importance of considering both enabling and inhibiting factors for the adoption of smart factory systems in the context of SMEs. Additionally, it has provided evidence that as the level of the smart factory system increases, the effect of perceived usefulness on user resistance decreases, thus making the transition to smart factory systems more challenging.

Agenda for knowledge creation within inter-project alliances and inter-firm supply chain networks has been extensively debated. However, the existing knowledge networks within consultant-supplier interfaces in the architecture, engineering and construction (AEC) industry seem to be vague, loose, incidental and insignificant. This study examines factors affecting knowledge networking intention (KNI) within construction service supply chain (CSSC) networks.

Data analysis was conducted on a quantitative survey of 161 consulting professional service firms in Tanzania, employing stepwise regression modelling as the statistical technique.

The results indicate that three types of knowledge inertia (KI) exert varying effects on KNI. While both procedural (PI) and learning inertia (LI) negatively impact KNI, experience inertia (EI) has no impact on KNI. In addition, knowledge governance (KG) mechanisms are found to strongly strengthen and leverage the negative effects of PI and LI on KNI and the positive link between EI and KNI within outbound and heterogeneous CSSC actors, with formal KG having greater leverage than informal KG.

The study offers guidance on how managers of PBOs should strategically orchestrate knowledge governance mechanisms within CSSC networks to leverage KI behaviours.

Current literature on KNI, KI and KG within CSSC networks offers a limited understanding of how KI behaviours influence KNI of project-based organizations (PBOs) in tapping vibrant outbound peripheral knowledge. The research presents two major original contributions. First, the empirical evidence contributes to deepening the current understanding of how heterogeneous external knowledge within consultant-supplier interactions is negatively influenced by KI. Lastly, the study suggests formal and informal knowledge governance strategies for managers on how to counteract KI forces, thus extending the theoretical debate on KNI, KI and KG literature.

This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.

The individual perspective of dynamic capabilities and family firms could be useful to shed light on the relationship between these topics, considering not only the heterogeneity of family businesses but above all the diversity of their collaborators, highlighting the underlying elements through which these firms are sustained.

This paper is based on systematic research, considering the most relevant literature about dynamic capabilities and family firms.

Findings highlight the individual perspective of dynamic capabilities and family firms, where we identify the main elements that family businesses must be aware of to be more innovative: high knowledge management/social capital, high entrepreneurial mindset/orientation, high tradition (retrospective and prospective), high empowering leadership, high next generation involvement, extended SEW (long-term perspective), risk-neutral, low conservative/inertia/paternalism and low emotionally attached.

The paper analyzes relevant studies on dynamic capabilities and family firms, proposing a research agenda with questions for further inquiries that cover inertia, paternalism, digital transformation and the individual perspective of dynamic capabilities and family firms. In addition, the authors provide practical implications for these topics.

Recently, interest and necessity for cloud-based hospital information systems (HISs) have emerged as an appropriate alternative for revitalizing medical information exchange between hospitals, analyzing “big data” medical information and developing the use of new medical technologies. The purpose of this paper is to investigate factors that affect the switching of information systems in existing on-premise environments into cloud-based HISs.

A research model was developed using the push–pull–mooring model based on migration theory. The research model was analyzed using confirmatory factor analysis and path analysis using partial least squares structural equation modeling.

The results of this study showed that low compatibility, perceived value, low cost and inertia influenced the intention to switch to cloud-based HISs; low flexibility and low compatibility influenced dissatisfaction; and low cost, ease of maintenance and ease of managing indicators influenced perceived value.

This study is expected to be used as the basis for developing a research model in subsequent studies to analyze the transition to new innovative technologies. Also, in practice, it is expected to contribute to the activation of cloud computing environments in hospitals.

This study looks to understand the opposing forces that would influence continuance intention. This is significant as users will take into account the positive and negative use experiences in determining their continuance intention. Therefore, this study looks to highlight the opposing forces of users’ continuance intention by proposing the Expectation-Confirmation-Resistance Model (ECRM).

Through an online survey, 411 responses were obtained from mobile payment users. Subsequently, a hybrid approach comprised of the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and Artificial Neural Network (ANN) was utilized to analyze the data.

The results revealed that all hypotheses proposed in the ECRM are supported. More precisely, the facilitating and inhibiting variables were found to significantly affect continuance intention. In addition, the ECRM was revealed to possess superior explanatory power over the original model in predicting continuance intention.

This study successfully developed and validated the ECRM which captures both facilitators and inhibitors of continuance intention. Besides, the relevance and significance of users’ innovative resistance to continuance intention have been highlighted. Following this, effective business and research strategies can be developed by taking into account the opposing forces that affect users’ continuance intention.