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The purpose of this paper is to explore mechanisms of the overseas marketing assets needed for marketing dynamic capability in Chinese multinational enterprises (MNEs) settings. Marketing assets of foreign subsidiaries contribute to the dynamic capability of MNEs, which are crucial for their sustained competitiveness. This kind of mechanism attracts much attention in academia and industry. However, there are few studies on how dynamic capabilities are developed in MNEs considering the organizational structure of geographically dispersed assets in multiple locations. This paper aims to examine the effect of knowledge-based and relational-based marketing assets on dynamic marketing capabilities and the mediating effect of customer orientation on Chinese MNEs.

Integrating the dynamic capability approach and the international marketing literature, this study examines the impact of two types of marketing assets of foreign subsidiaries, focusing on knowledge-based and relationship-based marketing assets, on the dynamic marketing capabilities of Chinese MNEs. A large-scale empirical study of Chinese MNEs operating in overseas markets was performed, and the questionnaires were distributed and collected.

The results suggest a positive impact of knowledge-based and relationship-based marketing assets on marketing dynamic capability. We find that customer orientation has a positive mediating effect on the relationship between marketing assets and marketing dynamic capability. We also find that the competitive strength of the overseas market negatively moderates this relationship.

This study aims to contribute to the existing literature with a more fine-grained understanding of marketing assets and marketing dynamic capability, then provides theoretical guidance and management suggestions for the formulation and implementation of internationalization strategies of Chinese MNEs.

The findings outline several important implications for MNEs seeking into expand to overseas markets.

This paper contributes a novel, combined perspective on marketing assets and marketing dynamic capability.

This study investigates how firms build strong dynamic marketing capability (DMC) from open innovation (OI) to enhance the performance of entrepreneurial firms. Moreover, this study unfolds DMC's mediating and moderating mechanisms underlying inbound and outbound OI and performance relationships, respectively.

To test the research model and hypotheses, this study drew a sample of 251 firms operating in Malaysia using the time-lagged survey method. Structural equation modelling was used in this study to investigate the model relationships.

The findings of this study reveal the positive interplay between inbound OI (knowledge acquisition) and DMC. The outbound OI (knowledge exploitation) in this study is found to mediate the relationship between inbound OI and firm performance. In addition, while the DMC has a mediating effect in the relationship between inbound OI and firm performance, such a capability reinforces the positive relationship between outbound OI and performance.

This study provides a noble insight into the complex interplay between OI and entrepreneurial firms' performance by developing and testing an integrated framework underpinned by a knowledge-based view and dynamic capability theory. The findings highlight the significance of taking an interdisciplinary and integrated approach to better understand the determinants of entrepreneurial firms' performance in an emerging country context.

The purpose of this paper is to develop a bi-objective optimization framework to select prefabricated construction service composition. An improved algorithm-genetic simulated annealing algorithm (GSA) is employed to demonstrate the application of the framework.

The weighted aggregate multi-dimensional collaborative relationship is used to quantitatively evaluate the synergistic effect. The quality of service is measured using the same method. The research proposed a service combination selection framework of prefabricated construction that comprehensively considers the quality of service and synergistic effect. The framework is demonstrated by using a GSA that can accept poor solutions with a certain probability. Furthermore, GSA is compared with the genetic algorithm (GA), simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO) to validate the performance.

The results indicated that GSA has the largest optimal fitness value and synergistic effect compared with other algorithms, and the convergence time and convergence iteration of the improved algorithm are generally at a low level.

The contribution of this study is that the proposed framework enables project managers to clarify the interactions of the prefabricated construction process and provides guidance for project collaborative management. In addition, GSA helps to improve the probability of successful collaboration between potential partners, therefore enhancing client satisfaction.

Although digital transformation (DT) has emerged as an important phenomenon for both research and practices, the influences remain inconclusive and inadequate. The emerging artificial intelligence (AI) technologies further complicate the understanding and practices of DT while understudied yet. To address these concerns, this study takes a process perspective to empirically investigate when and how digital-intelligence transformation can improve firm performance, aiming to enrich the literature on digital-intelligence transformation and strategic information systems (IS) field.

Drawing on the dynamic capability view and business agility, we took a process perspective to conceptualize and empirically examine the influence of digital-intelligence transformation and the process characteristics. Taking a continuous panel dataset of listed Chinese firms covering 2007 to 2020, we investigated digital-intelligence transformation’s effect on firm performance and the moderating roles of three strategic aspects: pace, scope and rhythm.

This study found that digital-intelligence transformation positively affects firm performance and is moderated by the characteristics of transformation processes (i.e. pace, scope and rhythm). Specifically, the high-paced and rhythmic transformation processes facilitate the positive relationship, while the large scope undermines the benefits of transformation. These relationships hold across various endogeneity and heterogeneity analyses.

Our findings provide valuable implications for digital-intelligence transformation and strategic IS field. First, this study enriches existing literature on digital-intelligence transformation by empirically investigating the influence from a process perspective. Moreover, this study provides insights into a comprehensive understanding of the complexity of digital-intelligence transformation and the influences of AI. Finally, this study provides practical implications on how to make digital-intelligence transformation to benefit firm performance.

The purpose of this study is to investigate the potential of using computer vision and deep learning (DL) techniques for improving safety on construction sites. It provides an overview of the current state of research in the field of construction site safety (CSS) management using these technologies. Specifically, the study focuses on identifying hazards and monitoring the usage of personal protective equipment (PPE) on construction sites. The findings highlight the potential of computer vision and DL to enhance safety management in the construction industry.

The study involves a scientometric analysis of the current direction for using computer vision and DL for CSS management. The analysis reviews relevant studies, their methods, results and limitations, providing insights into the state of research in this area.

The study finds that computer vision and DL techniques can be effective for enhancing safety management in the construction industry. The potential of these technologies is specifically highlighted for identifying hazards and monitoring PPE usage on construction sites. The findings suggest that the use of these technologies can significantly reduce accidents and injuries on construction sites.

This study provides valuable insights into the potential of computer vision and DL techniques for improving safety management in the construction industry. The findings can help construction companies adopt innovative technologies to reduce the number of accidents and injuries on construction sites. The study also identifies areas for future research in this field, highlighting the need for further investigation into the use of these technologies for CSS management.

Computer vision (CV) offers a promising approach to transforming the conventional in-person inspection practices prevalent within the construction industry. However, the reliance on centralized systems in current CV-based inspections introduces a vulnerability to potential data manipulation. Unreliable inspection records make it challenging for safety managers to make timely decisions to ensure safety compliance. To address this issue, this paper proposes a blockchain (BC) and CV-based framework to enhance safety inspections at construction sites.

This study adopted a BC-enhanced CV approach. By leveraging CV and BC, safety conditions are automatically identified from site images and can be reliably recorded as safety inspection data through the BC network. Additionally, by using this data, smart contracts coordinate inspection tasks, assign responsibilities and verify safety performance, managing the entire safety inspection process remotely.

A case study confirms the framework’s applicability and efficacy in facilitating remote and reliable safety inspections. The proposed framework is envisaged to greatly improve current safety inspection practices and, in doing so, contribute to reduced accidents and injuries in the construction industry.

This study provides novel and practical guidance for integrating CV and BC in construction safety inspection. It fulfills an identified need to study how to leverage CV-based inspection results for remotely managing the safety inspection process using BC. This work not only takes a significant step towards data-driven decision-making in the safety inspection process, but also paves the way for future studies aiming to develop tamper-proof data management systems for industrial inspections and audits.

Drawing an inference from institutional theory and dynamic capabilities view, this study empirically examined the impact of three institutional dimensions (regulative, normative and cognitive) and green entrepreneurial orientation (GEO) on a business firm’s performance. In addition, the moderating effect of dynamic capabilities on the relationship between GEO and firm performance was also explored.

The data were collected from 527 information technology (IT) firms in Pakistan using paper–pencil questionnaires, and the hypotheses were tested using structural equation modeling.

The findings showed that the regulative and normative institutional dimensions enhance GEO and firm performance in the selected developing country. However, the cognitive institutional dimension fails to report any substantial influence on GEO and firm performance. The findings raised concerns about lower individual accountability as well as the promotion of green practices and firm performance. In addition, dynamic capabilities positively moderate the GEO influence on firm performance.

With the interplay of institutional dimensions, GEO (as mediator) and dynamic capabilities (as moderator), this study developed and tested a unique framework to understand their influence on firm performance. Specifically, we extended the literature by giving evidence that among the three institutional dimensions, only regulative and normative are considered more important because of their direct and indirect (through GEO) positive effect on firm performance. In contrast, the cognitive institutional dimension failed to report any significant direct or indirect impact on firm performance in our study.

Tracking physical resources at the construction site can generate information to support effective decision-making and building production control. However, the methods for conventional tracking usually offer low reliability. This study aims to propose the integrated Smart Twins 4.0 to track and manage metallic formworks used in cast-in-place concrete wall systems using internet of things (IoT) (operationalized by radio frequency identification [RFID]) and building information modeling (BIM), focusing on increasing quality and productivity.

Design science research is the research approach, including an exploratory study to map the constructive system, the integrated system development, an on-site pilot implementation in a residential project and a performance evaluation based on acquired data and the perception of the project’s production team.

In all rounds of requests, Smart Twins 4.0 registered and presented the status from the formworks and the work progress of buildings in complete correspondence with the physical progress providing information to support decision-making during operation. Moreover, analyses of the system infrastructure and implementation details can drive researchers regarding future IoT and BIM implementation in real construction sites.

The primary contribution is the system proposal, centralized into a mobile app that contains a Web-based virtual model to receive data in real time during construction phases and solve a real problem. The paper describes Smart Twins 4.0 development and its requirements for tracking physical resources considering theoretical and practical previous research regarding RFID, IoT and BIM.

Strategy scholars have argued that microlevel behavioral decisions by firms play a disproportionate role in making a firm nimble. Central to this issue is the interplay among several factors, such as actions by individual actors, firm-level decisions and broader changes in the economic environment that lead to a firm being successful in a competitive environment. The purpose of this paper is to offer a theoretical exploration of microfoundations research and subject the idea to empirical analysis using the constructs of customer orientation, competitor orientation and technology orientation as microfoundations of strategy.

Data collected through a key informant survey of executives were tested through a hierarchical regression analysis.

The results of the study suggest that the microfoundations of strategy are located more in a firm’s customer and competitor focus, rather than a technological orientation. The findings also suggest that that customer orientation is a significant component of firm-level strategy and needs to be incorporated into decision-making in firms.

This study provides a framework that integrates the structural determinants of firm performance with microfoundations theory to refine our understanding of market knowledge capability.

The construction industry remains one of the most hazardous industries worldwide, with a higher number of fatalities and injuries each year. The safety and well-being of workers at a job site are paramount as they face both immediate and long-term risks such as falls and musculoskeletal disorders. To mitigate these dangers, sensor-based technologies have emerged as a crucial tool to promote the safety and well-being of workers on site. The implementation of real-time sensor data-driven monitoring tools can greatly benefit the construction industry by enabling the early identification and prevention of potential construction accidents. This study aims to explore the innovative method of prototype development regarding a safety monitoring system in the form of smart personal protective equipment (PPE) by taking advantage of the recent advances in wearable technology and cloud computing.

The proposed smart construction safety system has been meticulously crafted to seamlessly integrate with conventional safety gear, such as gloves and vests, to continuously monitor construction sites for potential hazards. This state-of-the-art system is primarily geared towards mitigating musculoskeletal disorders and preventing workers from inadvertently entering high-risk zones where falls or exposure to extreme temperatures could occur. The wearables were introduced through the proposed system in a non-intrusive manner where the safety vest and gloves were chosen as the base for the PPE as almost every construction worker would be required to wear them on site. Sensors were integrated into the PPE, and a smartphone application which is called SOTER was developed to view and interact with collected data. This study discusses the method and process of smart PPE system design and development process in software and hardware aspects.

This research study posits a smart system for PPE that utilises real-time sensor data collection to improve worksite safety and promote worker well-being. The study outlines the development process of a prototype that records crucial real-time data such as worker location, altitude, temperature and hand pressure while handling various construction objects. The collected data are automatically uploaded to a cloud service, allowing supervisors to monitor it through a user-friendly smartphone application. The worker tracking ability with the smart PPE can help to alleviate the identified issues by functioning as an active warning system to the construction safety management team. It is steadily evident that the proposed smart PPE system can be utilised by the respective industry practitioners to ensure the workers' safety and well-being at construction sites through monitoring of the workers with real-time sensor data.

The proposed smart PPE system assists in reducing the safety risks posed by hazardous environments as well as preventing a certain degree of musculoskeletal problems for workers. Ultimately, the current study unveils that the construction industry can utilise cloud computing services in conjunction with smart PPE to take advantage of the recent advances in novel technological avenues and bring construction safety management to a new level. The study significantly contributes to the prevailing knowledge of construction safety management in terms of applying sensor-based technologies in upskilling construction workers' safety in terms of real-time safety monitoring and safety knowledge sharing.