Collaborative Capabilities Research Articles

A maturity model to guide inter-organisational crisis management and response exercises

This paper proposes a six-step maturity ladder for inter-organizational collaborative capability in crisis management and response operations. The paper argues that collaborative crisis management and response can be seen as a case of complex adaptive systems, where awareness of the organizational context of crisis response, technical interoperability, and individual relations are drivers that enable rapid and successful mobilization of crisis response. The maturity ladder provides a link between the capabilities necessary for collaboration possessed by individual crisis response entities and the overall system maturity in terms of collaborative crisis management capability. It can inter alia be used as a basis for a discussion when inter-organizational exercises are appropriate and when focus must remain on the development of the capabilities of individual crisis response entities.

Fostering sustainability capabilities through experience: A case study on virtual mobility in STEM

For a 21st century facing cascading crises, including global pandemics, climate change, and social and economic disruption, education is more critical than ever. Universities, and consequently their curricula, have a responsibility to prepare all students and graduates to respond to and live within a disrupted, complex, and uncertain future. One way of preparing students to think and address complex global challenges is through international learning experiences. However, the global pandemic triggered an unforeseen disruption to student mobility and the acceleration of online learning environments, such as virtual mobility programs. To date there has been little exploration of how virtual mobility programs can be designed for science and their ability to foster sustainability capabilities within the discipline. This paper reports on the design (its curriculum and pedagogy) of an experiential virtual mobility program, designed and delivered during the pandemic. It illustrates an innovative, co-created, STEM-focused case study whereby learning focused on varied approaches to agricultural challenges and practices. Through the perspective of student participants, key education for sustainability capabilities of sustainability thinking, collaboration, affective learning, critical reflection, and interdisciplinary knowledge were analysed as themes and are discussed in relation to how these capabilities were shaped by the program design. We share this discussion to support and expand the use of further meaningful virtual experiences to foster sustainability capabilities in an international (online) setting by other University educators.

Multi-person interaction in collaborative virtual conference for Metaverse

Virtual conferences have successfully solved the challenges of traditional face-to-face conferences that can’t be carried out smoothly due to issues such as venue, transportation, and the pandemic. More importantly, as virtual conferences continue to develop and mature, they provide a virtual environment for multi-person collaboration, which is impossible to achieve with traditional face-to-face conferences. This technological innovation is expected to bring significant cost savings to various fields such as medical care, education, and industry. This paper proposes a unity-based multi-party collaborative virtual conference model. The model takes automobiles as the theme, which can realize the design and modification of the appearance of the automobiles by multiple people in the same space, and also supports operations such as the disassembly and installation of the automobile engine. This model is designed to deepen our understanding of multi-person collaboration capabilities in virtual conferences, a feature that is expected to significantly improve teamwork efficiency.

Cascaded Attention: Adaptive and Gated Graph Attention Network for Multiagent Reinforcement Learning.

Modeling the interactive relationships of agents is critical to improving the collaborative capability of a multiagent system. Some methods model these by predefined rules. However, due to the nonstationary problem, the interactive relationship changes over time and cannot be well captured by rules. Other methods adopt a simple mechanism such as an attention network to select the neighbors the current agent should collaborate with. However, in large-scale multiagent systems, collaborative relationships are too complicated to be described by a simple attention network. We propose an adaptive and gated graph attention network (AGGAT), which models the interactive relationships between agents in a cascaded manner. In the AGGAT, we first propose a graph-based hard attention network that roughly filters irrelevant agents. Then, normal soft attention is adopted to decide the importance of each neighbor. Finally, gated attention further refines the collaborative relationship of agents. By using cascaded attention, the collaborative relationship of agents is precisely learned in a coarse-to-fine style. Extensive experiments are conducted on a variety of cooperative tasks. The results indicate that our proposed method outperforms state-of-the-art baselines.

Building the Foundation for Creativity and Collaboration: Knowledge Sharing Learning Models

The integration of creativity, critical thinking, collaboration, and communication skills into 21st-century learning represents a pivotal goal in education, particularly within the realms of engineering. Despite this ambition, the actualization of creativity and collaborative capabilities among engineering students remains a significant challenge, primarily due to prevalent individualistic attitudes and apprehensions towards error in idea sharing. This study introduces and evaluates a Knowledge Sharing (KS) learning model aimed at overcoming these barriers, thereby facilitating enhanced creativity and collaboration. Employing the Akker learning stages, this model was implemented in an engineering education setting, yielding encouraging outcomes: students demonstrated increased motivation for interdisciplinary learning, acquired novel knowledge beyond their traditional curricula, and developed practical designs and tools responsive to community needs. The methodology section details the iterative process of model development, encompassing identification, design and preparation, implementation, replication, and dissemination phases, followed by a thorough validation process. Results indicate a positive impact on students' creative competencies and collaborative skills, underscoring the model's efficacy in fostering essential 21st-century skills.

Artificial Intelligence in Dermoscopy: Enhancing Diagnosis to Distinguish Benign and Malignant Skin Lesions.

This study presents an innovative application of artificial intelligence (AI) in distinguishing dermoscopy images depicting individuals with benign and malignant skin lesions. Leveraging the collaborative capabilities of Google's platform, the developed model exhibits remarkable efficiency in achieving accurate diagnoses. The model underwent training for a mere one hour and 33 minutes, utilizing Google's servers to render the process both cost-free and carbon-neutral. Utilizing a dataset representative of both benign and malignant cases, the AI model demonstrated commendable performance metrics. Notably, the model achieved an overall accuracy, precision, recall (sensitivity), specificity, and F1 score of 92%. These metrics underscore the model's proficiency in distinguishing between benign and malignant skin lesions. The use of Google's Collaboration platform not only expedited the training process but also exemplified a cost-effective and environmentally sustainable approach. While these findings highlight the potential of AI in dermatopathology, it is crucial to recognize the inherent limitations, including dataset representativity and variations in real-world clinical scenarios. This study contributes to the evolving landscape of AI applications in dermatologic diagnostics, showcasing a promising tool for accurate lesion classification. Further research and validation studies are recommended to enhance the model's robustness and facilitate its integration into clinical practice.

HWMP-based secure communication of multi-agent systems

Multi-agent systems (MAS), known for their autonomy, fault tolerance, and flexible collaboration capabilities, are widely used in various fields. Communication security is one of the most critical problems of MAS tasks. Once a malicious attacker invades agents in the system, it brings massive threats to the entire system. It tampers with routing messages, discards packets, and paralyzes the communication network. To implement collaboration tasks of MASs safely and efficiently, this work makes security improvements on the hybrid wireless mesh protocol (HWMP) with an additional authentication system. We enhance the proactive and reactive mode of the HWMP and apply it to an integrated system, i.e., the MAS formation control as a proper instance. We present a HWMP-based secure communication model (HSCM) for MASs. The theoretical analysis and simulation results demonstrate a significant enhancement in network performance under various threats, including packet loss rate, throughput, etc. The results indicate that HSCM plays a significant role in resisting common attacks (such as black hole and flooding attacks) when compared to multi-agent systems without any security protection. There is an approximate 30% increase in packet delivery rate, a substantial enhancement in throughput, and a reduction in routing overhead. The latency also fluctuates within reasonable bounds. Our solution provides secure communication for formation control under malicious attacks.

SUFFICIENCY OF HUMAN CAPITAL IN SME: EVOLUTION OF SUSTAINABLE COMPETITIVE ADVANTAGE

Objective: This research aimed to explore the concept of sustainable competitive advantage concept in small medium-sized enterprise (SME) with collaborative capability and entrepreneur resilience as a mediating variable. It examined the relationship between human capital owned by entrepreneurs and sustainable competitive advantage with a focus on the woven sector, one of the largest tourism-supporting sectors in Bali. Method: entrprenereurs of SMEs in Bali, Indonesia completed 333 surveys, with each construct measured using an adopted and modified scale from existing studies. Additional analyses were performed on the collected data using partial least square structural equation modelling (PLS_SEM) software. These analyses included regression, factor analysis, structural equation modelling with the boostrapping technique, reliability, validity, mediation and model fit indicates. Result: The results showed that the human capital of the entrepreneurs, which consisted of education and experience, cannot be a source of sustainable competitive advantage in SME due to low education levels and minimal experience in managing businesses. On the other hand, collaborative capability is one of capabilities needed to achieve sustainable competitive advantage because it helps overcome resource limitations and internal capability by collaborating with external parties. Furthermore, another dynamic capability needed is entrepreneur resilience which can help in dealing with environmental turbulence. This research further supports this assertion by showing a full mediation relationship, implying that the human capital of entrepreneurs is insufficient for SME to attain sustainable competitive advantage, necessitating collaborative capability and entrepreneur resilience as a mediating factor to achieve this objective.

A collaborative AR application for education: from architecture design to user evaluation

Augmented reality applications can be used in an educational context to facilitate learning. In particular, augmented reality has been successfully used as a tool to boost students’ engagement and to improve their understanding of complex topics. Despite this, augmented reality usage is still not common in schools and it still offers mostly individual experiences, lacking collaboration capabilities which are of paramount importance in a learning environment. This work presents an application called ARoundTheWorld, a multiplatform augmented reality application for education. It is based on a software architecture, designed with the help of secondary school teachers, that provides interoperability, multi-user support, integration with learning management systems and data analytics capabilities, thus simplifying the development of collaborative augmented reality learning experiences. The application has been tested by 44 students and 3 teachers from 3 different educational institutions to evaluate the usability as well as the impact of collaboration functionalities in the students’ engagement. Qualitative and quantitative results show that the application fulfils all the design objectives identified by teachers as key elements for augmented reality educational applications. Furthermore, the application was positively evaluated by the students and it succeeded in promoting collaborative behaviour. These results show that ARoundTheWorld, and other applications built using the same architecture, could be easily developed and successfully integrated into existing schools curricula.

The contribution of digital business strategy in enhancing collaborative innovation capability: The moderating role of organizational culture—A case study of six pharmaceutical companies in Jordan

AbstractWith innovation becoming more collaborative, the influence of digital business strategy (DBS) on interfirm cooperation has grown. This study investigates how DBS can enhance collaboration innovation capabilities across pharmaceutical companies in developing countries. Further, it investigates organizational culture as a moderating variable in the relationship between DBS and collaborative innovation capability (CIC). A total of 205 questionnaire responses were gathered on six Jordanian pharmaceutical corporations. The findings showed that each DBS element (development, objectives, resources, management capabilities, and digital leadership) positively affected CIC, and that organizational culture positively moderated the relationship between DBS and CIC. These results provide valuable insights for managers seeking to improve collaborative capability by leveraging digital business strategies and organizational culture.

Leveraging Generative AI Prompt Programming for Human-Robot Collaborative Assembly

In manufacturing, traditional robotic programming methodologies have often been focused on independent operation, offering limited capabilities for seamless human-robot collaboration. This paper introduces a paradigm shift in collaborative production systems by leveraging generative artificial intelligence (AI), specifically large language models (LLMs). Contrary to traditional methods that rely on pre-defined assembly instructions, this paper introduces a novel framework employing primitive knowledge of the production process, including product design and required assembly steps. By integrating LLMs and a behavior tree-based system control, this approach enables programmers to rapidly deploy collaborative assembly procedures by expediting the programming of robotic operations. The system also incorporates Natural Language Processing (NLP) technologies, which facilitate real-time alterations in assembly steps, leading to reduced overall production time. The framework’s behavior tree-based control architecture allows for dynamic adaptability, offering optimized solutions across a range of assembly scenarios. The results of the framework’s deployment suggest that this innovative programming paradigm significantly enhances both the adaptability and efficiency of collaborative manufacturing settings.

Vision-based human wrist localization and with Kalman-filter backed stabilization for Bilateral Teleoperation of Robotic Arm

The development of advanced robotic systems that can be operated effortlessly by humans is crucial for expanding the capabilities of human-robot interaction and collaboration. In this work, we propose a system that enables real-time and non-invasive tracking of the human wrist's position in three-dimensional space to facilitate an intuitive control of a remotely placed robotic arm, as an improvement towards efficient control mechanism. We leverage color segmentation based human wrist tracking in the viewing plane augmented with a stereo depth estimation for synthesising the localized wrist in the Cartesian space. The centroid of the segmented image is determined to generate the precise coordinates. To remove the variance in the estimated centroid, the trajectory of the localized points is modelled by Kalman filtering approach. Finally, the coordinates are transformed using Inverse Imaging Model and transmitted to an edge device (close to the robot), which then replicates the motion at the robot end using inverse kinematics. The results show a high degree of accuracy in tracking the wrist's movements, enabling precise and natural control over the robotic arm's motion. The system's adaptability to various environments and user populations is validated through tests with diverse subjects. With its high accuracy, real-time performance, the proposed approach holds great potential to enhance the efficiency and safety of human-robot collaborative applications across multiple domains.

Forking From the Future: How an Interorganizational Network Learned Its Way to New Software Business

Technological disruptions call for new capabilities beyond the reach of a single firm. How does a large interorganizational network learn its way to new Cloud software business while leveraging forking—that is, copying and branching of code common to software development? Such forking promotes commitment and innovation but may compromise joint learning in the network required for developing new capabilities under technological disruption. Elaborating a seminal learning theory in an interorganizational network context, we demonstrate how forking was about to sacrifice long-term aspirations to short-term interests early on. We contribute a new type of forking—forking from the future—and describe how this type of forking harnesses future aspirations and builds collaborative capabilities in the network while reducing tendencies for shortsightedness. Forking from the future consists of the introduction of external perspectives, the implementation of new rules, the use of integrative tools, and generally accelerating collaboration among the network participants from the future back (not from the present forward). As software becomes increasingly important across industries, forking from the future becomes foundational for future competitiveness.

Distribution-Independent Domain Generalization for Multisource Remote Sensing Classification.

The availability of multisource remote sensing data provides the possibility for comprehensive observation. Convolutional neural networks (CNNs) naturally integrate multisource feature extractors and classifiers into an end-to-end multilayer design. However, CNN assumes data are independent and identically distributed. In practice, it is not always possible to access the labels or even data of the testing scenes. Therefore, the CNN-based methods have exposed its limitation on generalization ability. To solve the issue, a feature-distribution-independent network (FDINet) is designed for multisource remote sensing cross-domain classification without feature alignment and decoupling operations. On one hand, an elegantly designed baseline is used for extracting multisource cross-domain features. The baseline extracts the common line and texture features through shallow weight-sharing networks. More importantly, the modality prediction probability is used to measure the similarity between the source domains and the target domains, thereby improving cross-domain collaboration capabilities. On the other hand, the sharpness-aware feature discriminating (SAFD) strategy is developed for model optimization. Specifically, the generalization ability is improved by minimizing the sharpness of local optima. To avoid the decrease in feature discrimination caused by the gradient conflict between sharpness and overall loss, the discrimination constraints are designed to balance feature discrimination and generalization ability. Comprehensive experiments are conducted on two datasets, which demonstrate that the proposed FDINet outperforms other competitors in terms of quantitative and qualitative analyses.

Impact of Supply Chain Management Practices on Innovative Performance: Mediating role of Organization Competence and Collaborative Capabilities as Moderator in SME Sector

Impact of Supply Chain Management Practices on Innovative Performance: Mediating role of Organization Competence and Collaborative Capabilities as Moderator in SME Sector

Dual-Level Framework for OpenBIM-Enabled Design Collaboration

Design coordination and collaboration are crucial in the architecture, engineering, and construction (AEC) industries, necessitating the integration of diverse disciplines and expertise to achieve unified and functional designs. Traditionally, these disciplines operate in isolation, leading to a fragmented design process. Building Information Modeling (BIM), recognized for its collaborative capabilities, presents an opportunity to revolutionize traditional design practices. However, existing research on BIM primarily assumes an ideal environment where all major participants use BIM models, overlooking the dynamics of mixed 2D Computer-aided Design (CAD) and 3D BIM environments. Addressing this research gap, this study aims to establish a dual-level OpenBIM-enabled collaborative design framework, enhancing the design process across various disciplines. The study employs a case study approach, applying this framework to an airport project in Chengdu, China. The airport includes different corridors that are similar in scope and scale but distinct enough to allow for a comparative study. The results demonstrate a 27% faster completion rate, a 98% reduction in design errors, and improved user satisfaction with the proposed method. The paper concludes by discussing the limitations of the study and suggesting avenues for future research.

Dynamic capabilities that matter for business failure versus survival

Due to the severity and length of the COVID-19 pandemic, some businesses have failed whereas others, including those in the same industry, have survived. Drawing on dynamic capability theory, we explored the dynamic capabilities, whose presence or absence are conditions for business failure or survival. We conducted 16 in-depth semi-structured interviews with owners/executives of firms from the travel and tourism, catering and hospitality, and agricultural export industries in India. Using fuzzy set qualitative comparative analysis (fsQCA) technique, we found three causal configurations for the business failure phenomenon, and two causal configurations for business survival phenomenon. The absence of collaborative capability with key stakeholders was observed as key to business failure, and the absence of leadership adaptive capability and the ability to leverage government support were found in two of the three causal configurations. In contrast, leadership adaptive capability and collaborative capability were present in the two causal configurations for business survival. Contrary to common viewpoints, digital transformation capability was neither sufficient to prevent failure nor necessary to ensure survival. By focusing on firms' dynamic capabilities as the conditions that differentiate business failure from survival, this study advances scholarship, and offers guidance to managers on navigating through a crisis.

Perspective Taking Reflects Beliefs About Partner Sophistication: Modern Computer Partners Versus Basic Computer and Human Partners.

We investigate partner effects on spatial perspective taking behavior in listeners, comparing behavior with a human versus a computer partner (Experiments 1 and 2), and with computer partners of different perceived capabilities (Experiment 3). Participants responded to spoken instructions from their partner which could be interpreted egocentrically (from their own perspective) or othercentrically (from their partner's perspective). In contrast to earlier work, we found that participants were more egocentric with a computer than a human partner. Participants were also more egocentric with a computer partner that appeared more modern and capable, compared to one that appeared outdated and limited in ability. Our results show that perspective taking behavior is sensitive to information about one's partner; in particular, listeners consider their partner's potential ability to collaborate, adjusting their egocentric tendencies accordingly. Moreover, we highlight what appears to be a shift in listeners' expectations regarding computers' collaborative capabilities, leading to greater willingness to push the burden of perspective taking onto a computer partner.

Research on Collaborative Innovation Evaluation of Intelligent Logistics Park

The collaborative innovation capability of intelligent logistics parks plays a crucial role in promoting their development, but still encounters various problems in terms of progress. On the basis of summarizing the evaluation indexes and methods of collaborative innovation capability in logistics systems, this article constructs an evaluation index system from three dimensions of intelligence, collaboration capabilities, and innovation capabilities using the combined principal component analysis and data envelopment analysis (DEA). In this empirical article, 18 intelligent logistics parks in the upper, middle, and lower reaches of the Yangtze River Economic Belt are taken as the research objects to analyze the key factors influencing collaborative innovation of practical intelligent logistics parks. Results show that, on the one hand, the collaborative innovation process of many intelligent logistics parks have redundant inputs and outputs, which leads to failure of realizing DEA effectively; on the other hand, gaps in the collaborative innovation level leads to failure of realizing the overall coordinated development. The level of economic development cannot completely determine the level of collaborative innovation of the intelligent logistics park.

An ETH-based approach to securing industrial Internet systems against mutinous attacks

In modern manufacturing industries, industrial components are becoming increasingly open and interconnected which significantly promotes the collaboration capability and producing efficiency on one hand, while, on the other hand, makes the industrial internet more vulnerable to various threats and attacks. In order to defend a distributed industrial Internet network system against two kinds of typical mutinous attacks, i.e., Byzantine attacks and DDoS attacks, that happen inside of the system, this paper proposes an Ethereum-based securing strategy. First, a credit mechanism-based Bayesian inference method is developed to increase the system nodes' sensitivity to malicious behavior and to improve system's robustness against false messages. Then, a miner selection method is proposed to avoid the information clog occurring in the system nodes' txpools and improve the efficiency of the whole system. The constructed securing strategy consists of these two methods and is shown to be applicable to industrial scenarios involving both mobile and static nodes. Several simulations are presented to verify effectiveness of the proposed approach. It is found that the accuracy of identifying false messages broadcast by Byzantine attackers is about 90%.