Core Assets Research Articles

The relationship among the innovation environment, transactive memory system of the R&D team, and knowledge collaboration

The innovation environment is the basis for the operation of the innovation ecosystem. In an era where knowledge resources are increasingly recognized as core assets, the advent of transactive memory system (TMS) has significantly enhanced the knowledge collaboration among R&D (Research & Development) teams, thereby boosting their innovation performance. Based on the empirical analysis of 235 valid questionnaires, this paper explores the relationship among the innovation environment, R&D Team's TMS, and knowledge collaboration. The results show that: (1) the Innovation environment has a direct and significant positive effect on the team's TMS and knowledge collaboration; (2) Team's TMS has some direct and significant positive effects and mediating effects on Knowledge Collaboration, and the Coordination of team's TMS has no significant effect on the Knowledge Integration process of Knowledge Collaboration; (3) The innovation environment can indirectly affect the knowledge collaboration process through the Specialization and Credibility of the TMS. This study further enriches the relevant research in the field of knowledge management and provides theoretical support and countermeasures for enterprises to promote innovation and development by optimizing knowledge management.

Software product line testing: a systematic literature review

A Software Product Line (SPL) is a software development paradigm in which a family of software products shares a set of core assets. Testing has a vital role in both single-system development and SPL development in identifying potential faults by examining the behavior of a product or products, but it is especially challenging in SPL. There have been many research contributions in the SPL testing field; therefore, assessing the current state of research and practice is necessary to understand the progress in testing practices and to identify the gap between required techniques and existing approaches. This paper aims to survey existing research on SPL testing to provide researchers and practitioners with up-to-date evidence and issues that enable further development of the field. To this end, we conducted a Systematic Literature Review (SLR) with seven research questions in which we identified and analyzed 118 studies dating from 2003 to 2022. The results indicate that the literature proposes many techniques for specific aspects (e.g., controlling cost/effort in SPL testing); however, other elements (e.g., regression testing and non-functional testing) still need to be covered by existing research. Furthermore, most approaches are evaluated by only one empirical method, most of which are academic evaluations. This may jeopardize the adoption of approaches in industry. The results of this study can help identify gaps in SPL testing since specific points of SPL Engineering still need to be addressed entirely.

Identifying Reusable Core Assets of Digital Health Apps.

We aim to identify and model reusable core assets to facilitate the development of a number of similar, but adapted DHAs in the context of an initial product line engineering approach. To identify core assets, we apply a systematic analysis of six exemplary state-of-the-art DHAs. In an iterative process, they were modeled in a feature model. We identified 14 core assets of DHAs out of which six are mandatory (i.e. required by each DHA) and eight are optional core assets (i.e. required by most DHAs, depending on the app complexity). We found that DHAs share common functionalities that could contribute to a more efficient development of the DHA, especially in terms of time and cost savings.

Excess goodwill and enterprise litigation risk

Corporate mergers and acquisitions (M&A) are now a common strategic choice for enterprises. As such, goodwill, which is a core asset of M&A activities, is pivotal for financial valuation and accounting. However, the phenomenon of ‘excess goodwill’, resulting from overvaluation due to management overconfidence and performance promises, poses significant risks, including potential financial statement distortions and increased litigation. This study investigates the intrinsic link between excess goodwill and corporate litigation risk by utilising theoretical analyses and empirical tests. By analysing data from A-share listed companies in Shanghai and Shenzhen from 2007 to 2022, we employed the regression residual method to measure excess goodwill and determine its impact on litigation risk through mediating factors such as financing constraints, risk-taking and agency costs. The findings indicate that excess goodwill significantly increases litigation risk, with a more pronounced effect on manufacturing firms and those with low internal control quality. This research provides valuable insights into optimising goodwill accounting treatment and enhancing enterprise risk management practices. The study's implications suggest that stricter internal controls and cautious goodwill valuation practices are essential to mitigate risks, ultimately contributing to the stability of the capital market and the protection of investor interests.

The Influence of Innovative Resources on the Comprehensive Carrying Capacity of China’s Urban Agglomerations: A System Dynamics Perspective

The sustainable development of urban agglomerations greatly relies on their comprehensive carrying capacity (CCC). As society evolves, innovative resources emerge as core assets and serve as crucial pillars of this capacity. Despite existing CCC studies, the influence of innovative resources remains underexplored. This study analyzes the influence of innovative resources on the CCC of 19 urban agglomerations in China using a system dynamics approach. We find that innovative resources are an important subsystem of CCC. Increasing innovative resources is an effective strategy for enhancing CCC, yet the effects of different types of innovative resources vary. Merely increasing the number of universities and research institutions does not significantly improve the CCC level. Increasing the expenditures of higher education institutions, internal R&D, and the number of patents are effective approaches to enhance CCC. Moreover, these factors can form a virtuous cycle, mutually promoting innovation and CCC development, thus injecting new momentum into the sustainable development of urban agglomerations.

“Run Forrest Run!”: Measuring the Impact of App-Enabled Performance and Social Feedback on Athletic and Usage Outcomes

Exercise-tracking apps are digital tools for delivering personalized behavioral interventions. Despite the growing usage of exercise applications, the efficacy of in-exercise app features in driving usage and athletic outcomes remains poorly understood. To remain competitive, sports organizations now need to leverage tracking tools to efficiently allocate resources and streamline training regimens and interventions for their core assets (i.e., athletes). In response to these operational needs, we examine two specific forms of such in-exercise interventions, namely performance feedback and social feedback. We conducted an 18-month-long field study with 1,037 uniformed group servicemen to assess the effect of these feedback types on running and usage outcomes. Results from the field study provided evidence that these two app features improved the servicemen’s running times and frequency of application usage, on average. Contrary to the common belief that more features are better, the joint usage of two feedback features does not produce additive effects. Tests at more granular levels suggest that users who received both feedback types in exercise episodes exhibit overconfidence behavior by participating in fewer subsequent exercises. The receipt of both feedback may be redundant and can cause user annoyance. Heterogeneity tests revealed that while performance feedback benefited most runners, social features were effective only for already stronger runners. Also, only positive social feedback had a significant impact on running performance. The results further indicate that performance feedback generated a slow but sustained increase in usage frequency, while social feedback spurred quick initial growth in usage but dwindled in effectiveness over time. Implications for theory and practice, as well as directions for further research, are discussed.

Reduction of precious metal ions in aqueous solutions by contact-electro-catalysis

Precious metals are core assets for the development of modern technologies in various fields. Their scarcity poses the question of their cost, life cycle and reuse. Recently, an emerging catalysis employing contact-electrification (CE) at water-solid interfaces to drive redox reaction, called contact-electro-catalysis (CEC), has been used to develop metal free mechano-catalytic methods to efficiently degrade refractory organic compounds, produce hydrogen peroxide, or leach metals from spent Li-Ion batteries. Here, we show ultrasonic CEC can successfully drive the reduction of Ag(ac), Rh3+, [PtCl4]2-, Ag+, Hg2+, Pd2+, [AuCl4]-, and Ir3+, in both anaerobic and aerobic conditions. The effect of oxygen on the reaction is studied by electron paramagnetic resonance (EPR) spectroscopy and ab-initio simulation. Combining measurements of charge transfers during water-solid CE, EPR spectroscopy and gold extraction experiments help show the link between CE and CEC. What’s more, this method based on water-solid CE is capable of extracting gold from synthetic solutions with concentrations ranging from as low as 0.196 ppm up to 196 ppm, reaching in 3 h extraction capacities ranging from 0.756 to 722.5 mg g−1 in 3 h. Finally, we showed CEC is employed to design a metal-free, selective, and recyclable catalytic gold extraction methods from e-waste aqueous leachates.

Enhancing capital market efficiency: The role of data assets disclosure in reducing stock price synchronicity

In the burgeoning digital economy, data have emerged as a pivotal factor of production, embodying a critical source of competitive advantage and core assets for companies. This study investigates the influence of data assets disclosure on the efficiency of capital market pricing, particularly through the lens of stock price synchronicity among Shanghai and Shenzhen A-share listed companies from 2013 to 2021. The analysis reveals that transparent data assets information significantly diminishes stock price synchronicity. The reduction is more pronounced when the disclosed data assets information is highly verifiable and comprehensible. Mechanistic exploration suggests that this effect primarily arises from diminished information asymmetry, enhanced long-term investments by institutional investors, and eased financing constraints. Notably, the impact is more substantial in non-high-tech companies and those with superior information disclosure ratings. After rigorous robustness checks and endogeneity considerations, our findings persist, highlighting the critical function of data assets disclosure in reducing stock price synchronicity and offering actionable insights for refining corporate information disclosure and governance practices.

The RiskTole Model for Future Financial Inclusion-Literacy?

Without proper planning, individual face financial hardship when reach golden age. Financial planning is a dynamic scenario, whereby complex integration both external setting and internal consideration. Therefore, academician and practitioners confront challenge to comprehensive framework integration. This study intent to develop an inclusive framework, in which integrate financial planning and behaviour, to accommodates human-life cycle objectives. This study data collection used mixed method convergent design multiple sources. To support the development of RiskTole framework, model consists of financial planning, hierarchy of needs, and financial behaviour model is being discussed. The framework incorporates three elements, namely time period, anticipated events, and risk tolerance. The framework includes two layer, whereby inner layer includes four core assets (asset management, protection, accumulation and distribution), subsequent identify of six financial planning areas. Outer layer layout financial decision choice for the planning. Finally, four supplement recommendations by respondents, comprises rebalancing EPF-collateral profit rate, financing repayment incremental, bi-weekly operation transaction, and sinking fund creation. The framework offers originality by providing body of knowledge from new dimension, and support Sustainable Development Goals 2023 financial inclusion initiative. Nevertheless, the success implementation entails public and private long-term support, accessibility inclusion of proper financial tools, and knowledgeable practitioner to serve.

The role of BIM and GIS in HS2 historic environment data management, an overview of HS2 Phase 1, UK

The HS2 historic environment programme undertaken for Phase One of HS2 between London and the West Midlands has resulted in a substantial digital archive, including Geographic Information Systems (GIS) data. According to the BIM (Building Information Modelling) approach, HS2 historic environment assets are considered as part of the construction assets, alongside the other disciplines assets such as highways, bridges, tunnels, and fencing. The GIS and spatial data play the role of a glue to demonstrate the interrelationship and hierarchy between archaeological assets, recording their location and geometry. Designating a unique asset ID (UAID) to each archaeological asset, and joining them to their attributes table and relating documents, creates a relationship between historic environment assets GIS data and their respective non-GIS data. According to HS2 digital engineering with BIM approach, HS2 historic environment core and primary assets have been identified, which the hierarchical order of them is as follows: Location Specific Written Scheme of Investigation (LS-WSI) and Project Plans (PPs) as core assets, and Written Scheme of Investigation Interventions (WSI-Interventions), Archaeological Features, and Archaeological Objects as historic environment primary assets. Such an efficient, transparent, and readable asset data structure provides a lasting and valuable legacy for the lifecycle of the project digital data. Four different systems combine to form the digital legacy of the project, which complement the physical archive. These four systems are: HS2 Asset Information Management System (AIMS) and GIS systems, as well as Online Access to the Index of Archaeological Investigations (OASIS), and supporting digital data curated with the Archaeological Data Service (ADS) systems. As significant parts of the programme legacy, HS2's historic environment physical and digital archive establish an unprecedented opportunity for knowledge creation.

Detecting and Visualizing Implementation Feature Interactions in Extracted Core Assets of Software Product Line

Detecting and Visualizing Implementation Feature Interactions in Extracted Core Assets of Software Product Line

The Debt Problem of Evergrande

Evergrande Real Estate Group Co., Ltd. was once a leading enterprise in China's real estate industry and one of the Fortune 500 companies. However, in the past few years, Evergrande fell into a huge debt crisis and was on the brink of bankruptcy. Although with the joint efforts of the leaders and employees of Evergrande Group, all core assets of Evergrande Group have been preserved, which allowing the company to continue normal operations. But the debt issue remains the biggest problem for Evergrande Group. This study conducted a survey and analysis based on the performance of Evergrande over the past 30 years, attempting to identify the reasons for Evergrande's two trillion yuan debt crisis. Based on the theories of economists and entrepreneurs' experiences, a solution to Evergrande's debt crisis can be integrated. This study will conduct a detailed analysis of the three main causes of Evergrande's debt crisis, including high leverage profit model, diversified development, and excessive dividends. The author will collect resources through online search, book browsing, and interviews with professionals, and then present them in the form of papers.

Inventory management of battery swapping and charging stations considering uncertainty

The battery swapping mode of electric vehicles (EVs) is expected to play an essential role in transportation and power systems. Plenty of batteries are managed by the battery swapping and charging stations (BSCSs) as the core assets. Proper inventory scale and charging/discharging control of batteries are essential to the planning and operation of BSCSs. This paper addresses two critical aspects of BSCS batteries: the optimal amount of inventory batteries and the tradeoff between the initial number of depleted and fully-charged batteries at the beginning of each scheduling horizon. Aiming at these, the time coupling between initial inventory, charging/discharging strategy, and swapping time sequence is analyzed. Afterward, it establishes the initial inventory based charging/discharging (IIC) model. The uncertain swapping demand is fully considered by utilizing a data-driven distributionally robust optimization (DRO) approach with an improved K-means clustering algorithm. A duality-free column-and-constraint generation (C&CG) algorithm solves the problem iteratively. The simulation results demonstrate the validity of the IIC model and show that the obtained optimization results achieve the balance of economy and robustness. Moreover, the impact of battery technology development on inventory batteries is analyzed, and suggestions are given.

Bespoke Virtual Machine Orchestrator: An Approach for Constructing and Reconfiguring Bespoke Virtual Machine in Private Cloud Environment

A cloud-computing company or user must create a virtual machine to build and operate a cloud environment. With the growth of cloud computing, it is necessary to build virtual machines that reflect the needs of both companies and users. In this study, we propose a bespoke virtual machine orchestrator (BVMO) as a method for constructing a virtual machine. The BVMO builds resource volumes as core assets to meet user requirements and builds virtual machines by reusing and combining these resource volumes. This can increase the reusability and flexibility of virtual-machine construction. A case study was conducted to build a virtual machine by applying the proposed BVMO to an actual OpenStack cloud platform, and it was confirmed that the construction time of the virtual machine was reduced compared with that of the existing method.

AMINO: A quality assessment framework for modeling ecosystems

SummaryModels are core assets in Model‐Driven Engineering (MDE). They are pervasively used throughout software development processes to leverage automation, increase cost‐effectiveness, and enhance quality factors. Model repositories have been successfully proposed to enforce reuse and elicit correlations among modeling artifacts, enabling storing operations on model‐based artifacts and collaborative modeling features. Maintaining and improving the quality of modeling artifacts is mandatory for software quality scale‐ups. Limiting the exploration of datasets and repositories of models to individual artifacts might reduce the ability to capture insights and reuse opportunities. This paper proposes AMINO, an analytics tool for model repositories supporting the discovery and quality evaluation of modeling ecosystems.

Agile Software Development and Reuse Approach with Scrum and Software Product Line Engineering

Agile methods and software product line engineering (SPLE) are widely recognized as practical approaches for delivering high-quality software, adapting to evolving stakeholder needs, and tackling complex problems. This study proposes a hybrid agile software development and reuse approach called SPLE-Scrum based on the activities of software product line engineering and Scrum. Within the SPLE process, we incorporate requirement engineering and design practices to create a reference architecture with reusable components called core assets by introducing a product management meeting. The core assets are reused to build a series of applications with various product lines. The product increments are delivered in each Sprint with the review and retrospective meetings based on Scrum lifecycle and practices. We present a case study involving a blockchain online store to demonstrate the practical application of SPLE-Scrum, highlighting the benefits of integrating Scrum and software product line engineering. The research hypotheses of the proposed approach were validated through a study of structured interviews with 5 experts and 44 software practitioners, showing that the key factors of product management, project requirements, and product architecture in the SPLE-Scrum approach have a beneficial impact on project success. The SPLE-Scrum approach provides valuable insights and practical guidance for organizations seeking to optimize their software engineering practices while incorporating agile development and software reuse capabilities.

Virtualising labs in engineering education: a typology for structure and development

ABSTRACT The use of virtual labs in higher education is gaining growing interest, with different debates in the literature about their role in addressing learning outcomes and balancing hands-on activities. This study seeks to understand how labs can be virtualised and thus structured to contribute to engineering education, by adopting an innovative perspective in studying the labs themselves as core assets to be developed for teaching and learning. Following the precepts of grounded theory, we performed a multi-case study of nine labs that underwent a process of virtualisation and their role within three programs of engineering education. Findings revealed (1) the dynamics in uncovering and exploiting the potentialities of different virtualisation paths, by overcoming difficulties in funding or a wider use in different courses, (2) the structural needs, such as stakeholder collaboration specifics and technical update intensity, and (3) the importance of education and research specifics in driving the design and development of virtualised labs. The pattern analysis of the relation between these features guided the development of a typology of virtualised labs that can be ascribed to three structuring phases – identified as foundational, intermediate, and advanced – and constitute the key contribution of this paper for both theory and practice.

Cognitive-Based Crack Detection for Road Maintenance: An Integrated System in Cyber-Physical-Social Systems

Effective road maintenance can not only achieve a balance between limited resources and long-term high-efficiency performance of road but also reduce the loss of life and property caused by road damage to vehicles and pedestrians. Due to the lack of a multidimensional dynamic monitoring system and enough extremely special data, the existing road maintenance system cannot accurately assess the road surface condition and provide timely early warning of sudden road damage. In this article, the M-RM system is proposed, that is, a metaverse-enabled road maintenance system based on cyber–physical–social systems (CPSSs), which fully utilizes the social and artificial system information of CPSS, as well as the simulation, monitoring, diagnosis and prediction functions of road systems in the virtual world of the metaverse. Then, in the road damage detection of system model in the virtual world, for the virtual data of the core assets of the metaverse, we propose an adaptive and information-preserving data augmentation (AIDA) algorithm-based nonclassical receptive field suppression and enhancement, an algorithm developed from human visual cognition. This algorithm enables the generation of a large amount of scarce fidelity data and avoids the introduced noise from impairing the performance of nonaugmented data. Finally, a crack detection algorithm named pay attention twice (PAT) is proposed, which uses the generated virtual data for training, and achieves secondary attention to high-frequency targets by fusing frequency-division convolution and mixed-domain attention mechanism. The detection performance of small targets in uncertain environments is enhanced. The metaverse system built in the current research can not only be used for road maintenance but also empower the traffic metaverse by using the traffic flow prediction module embedded in the algorithm. Experimental results demonstrate that the proposed algorithm can be applied to the road damage detection task under different noise and weather conditions, and the performance outweighs other state-of-the-art algorithms.

Design of embedded software architecture for spacecraft electric propulsion system

With the rapid growth of the number of spacecraft tasks and the complexity of the system, spacecraft software development is faced with the challenges of high-quality and rapid delivery, increased complexity, and frequent changes in requirements. The reuse rate of software assets needs to be improved urgently. In order to realize cross-platform and cross-project reuse of software design, this paper studies the design of electric propulsion software architecture. Carry out requirements decomposition and subsystem division of electric propulsion systems for different platforms, extract common requirements and variability requirements at the system level and subsystem level based on the Feature-Oriented Domain Analysis method, and establish a requirements model. Based on the requirements model, an electric propulsion software architecture integrating “event-driven + components” is proposed, and the classic event-driven model of “publish-subscribe” is adaptively improved. The architecture has been instantiated and applied to 16 projects on 4 platforms, and the reuse rate of core assets has reached 70%. This paper has certain guidance and reference significance for spacecraft software asset reuse and platform construction.

THE MECHANISM FOR INCREASING THE EFFICIENCY OF MACHINE-BUILDING ENTERPRISES IN A COMPETITIVE ENVIRONMENT

The article delves deeply into the significance of machine-building in Ukraine’s economy, emphasizing its profound impact on the Gross Domestic Product and the overarching national economic security. It sheds light on the pivotal role of cutting-edge technologies, the essence of production automation, and the imperativeness of intellectualization in bolstering an enterprise’s competitive stance in the market. The research underscores the paramount importance of strategic evolution, the infusion of product innovations, and the relentless modernization of the enterprise’s core assets. Such endeavors not only cater to contemporary market demands but also fortify the enterprise’s position, ensuring its sustained growth and relevance in an ever-evolving economic landscape. The article further explores the challenges faced by the machine-building sector, the potential solutions to overcome these challenges, and the future prospects of this vital industry in the context of global trends and technological advancements. Additionally, it delves into the intricate interplay between policy-making, industry standards, and the role of innovation in shaping the trajectory of the machine-building sector in Ukraine. The research also provides insights into market dynamics, competitive strategies, and the potential pathways for the industry to navigate the complexities of the global market. Emphasis is placed on understanding the global context, the role of research and development, and the importance of fostering a culture of continuous improvement and innovation within the industry. The article also discusses the potential of collaboration between industry stakeholders, the role of government in facilitating growth, and the need for a holistic approach to address the multifaceted challenges faced by the sector.