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In the context of constructing an integrated national strategic system, collaborative innovation among enterprises is the current social focus. Therefore, in order to find the interest relationship between multiple game subjects, to explore the influencing factors of collaborative innovation of civil-military integration enterprises. This paper constructs a collaborative innovation mechanism for military–civilian integration involving four game subjects (military enterprises, private enterprises, local governments, and science and technology intermediaries). It aims to solve and reveal the evolutionary game relationship among the four parties.

To explore the mechanism of military–civilian collaborative innovation involving four players, this study employs game theory and constructs an evolutionary game model for collaborative innovation with the participation of military enterprises, civilian enterprises, local governments, and technology intermediaries. The model reveals the evolutionary game patterns among these four entities, analyzes the impact of various parameters on the evolutionary process of the game system, and numerical simulation is used to show these changes more specifically.

The research findings demonstrate that active government subsidies promote cooperation throughout the system. Moreover, increasing the input-output ratio of research and development (R&D), the rate of technological spillovers, and the R&D investment of civilian enterprises all facilitate the tendency toward cooperation within the system. However, when the government chooses to actively provide subsidies, increasing R&D investment in military enterprises may hinder the tendency toward cooperation. Furthermore, central transfer payments, government punishment from the central government, and an increase in the information conversion rate of technology intermediaries may suppress the rate of cooperation within the system.

Most of the previous studies on the collaborative innovation of military–civilian integration have been tripartite game models between military enterprises, private enterprises, and local governments. In contrast, this study adds science and technology intermediaries on this basis, reveals the evolution mechanism of collaborative innovation of civil-military integration enterprises from the perspective of four-party participation, and analyzes the factors influencing the cooperation of the whole system. The conclusion of this study not only enriches the collaborative innovation evolution mechanism of military–civilian integration enterprises from the perspective of multiple agents but also provides practical guidance for the innovation-driven development of military–civilian integration enterprises.

The purpose of this paper is to describe the design and development of “Pylon-Climber II”, a 5-DOF biped climbing robot (degree of freedom – DOF) for moving on the external surface of a tower and assisting the electricians to complete some maintenance tasks.

The paper introduces a pole-climbing robot, which consists of a 5-DOF mechanical arm and two novel grippers. The gripper is composed of a two-finger clamping module and a retractable L-shaped hook module. The robot is symmetrical in structure, and the rotary joint for connecting two arms is driven by a linear drive mechanism.

The developed prototype proved a new approach for the inspection and maintenance of the electricity pylon. The gripper can reliably grasp the angle bars with different specifications by using combined movement of the two-finger clamping module and the retractable L-shaped hook module and provide sufficient adhesion force for the Pylon-Climber II.

The clamping experiments of the gripper and the climbing experiments of the robot were carried out on a test tower composed of some angle bars with different specification.

This paper includes the design and development of a 5-DOF biped climbing robot for electricity pylon maintenance. The climbing robot can move on the external surface of the electric power tower through grasping the angle bar alternatively. The gripper that is composed of a two-finger gripping module and a retractable L-shaped hook module is very compact and can provide reliable adhesion force for the climbing robot.

The purpose of this paper is to describe the design and development of “Pylon-Climber”, a pole climbing robot (PCR) for climbing along the corner columns of electricity pylon and assisting the electricians to complete maintenance tasks.

Introduces a PCR that is composed of a simple climbing mechanism and two novel grippers. The gripper consists of two angle-fixed V-blocks, and the size of V-block is variable. The clamping method of the angle bar meets the requirement of the force closure theorem. The whole design adopts symmetrical design ideas.

The developed prototype proved possibility of application of PCRs for inspection and maintenance of pylon. The novel gripper can provide enough adhesion force for climbing robot.

The robot is successfully tested on a test tower composed of different specification steel angles, oblique ledges and overlapping steel struts.

Design and development of a novel climbing assistive robot for pylon maintenance. The robot is able to climb along the column of electricity pylon and pass all obstacles. The gripper can reliably grasp the angle bar with different specification and overlapping steel struts from multiple directions.

This study's purpose is to propose an integrated post-adoption model based on expectation-confirmation model (ECM) and cognitive absorption (CA) theory to examine whether network factors, gamification factor, and quality factors as antecedents to end-users' beliefs can affect their continuance intention of the robo-advisor.

A total of 600 questionnaires were distributed in three sample banks in Taiwan, and sample data for this study were collected from these three banks' customers who had experience in using these banks' own robo-advisor to make their investment decisions. Consequently, 381 useable questionnaires were analyzed using structural equation modeling in this study, with a useable response rate of 63.5%.

This study proposes a solid research model that based on ECM and CA theory, three types of factors, network factors, gamification factor, and quality factors, as antecedents to end-users’ continuance intention of the robo-advisor have been examined, and this study's results strongly support the research model with all hypothesized links being significant.

This study contributes to end-users' continuance intention of the robo-advisor based on ECM, CA theory, theory of network externalities, gamification, and updated DeLone and McLean IS success model, and reveals deep insights into the evaluation of determinants in the field of end-users' continuance intention of the robo-advisor. Hence, it is especially worth mentioning that three types of determinants (i.e. network factors, gamification factor, and quality factors) are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into account in this study's research model development of end-users' continuance intention of the robo-advisor to acquire a more all-round and robust analysis.

Three-dimensional (3D) printing provides more possibilities for composite manufacturing. Composites can no longer just be layered or disorderly mixed as before. This paper aims to introduce a new algorithm for dual-material 3D printing design.

A novel topology design method: solid isotropic material with penalization (SIMP) for hybrid lattice structure is introduced in this paper. This algorithm extends the traditional SIMP topology optimization, transforming the original 0–1 optimization into A–B optimization. It can be used to optimize the spatial distribution of bi-material composite structures.

A novel hybrid structure with high damping and strength efficiency is studied as an example in this work. By using the topology method, a hybrid Kagome structure is designed. The 3D Kagome truss with face sheet was manufactured by selective laser melting technology, and the thermosetting polyurethane was chosen as filling material. The introduced SIMP method for hybrid lattice structures can be considered an effective way to improve lattice structures’ stiffness and vibration characteristics.

The fabricated hybrid lattice has good stiffness and damping characteristics and can be applied to aerospace components.

This study aims to propose a quantitative approach to reduce the number of suppliers in an organization. This method is based on grouping, and different parts are grouped based on the capabilities they need and are allocated to suppliers who have these capabilities. In this regard, an integrated model for supplier reduction and grouping of parts using a group technology-based algorithm is proposed.

Design science research methodology was used in this study. The main problem under investigation is a large number of suppliers in an organization’s supply base. The proposed model was used to solve this problem in the electric motor industry.

The results of implementing the proposed model in the electric motor industry showed that reducing suppliers had a significant effect on reducing cost, increasing information sharing, increasing supplier innovation and technology, enhancing the relationship between buyers and sellers and reducing risks in the production process.

From a managerial point of view, reducing the number of suppliers plays an important role in the company’s overall strategy, and seems to be a prerequisite for building a strong supplier partnership and an effective supply chain, and will have many benefits for the focal company and suppliers.

To the best of the authors’ knowledge, grouping and formation of product families have never been performed based on the similarity of the operational capabilities required for producing parts, and it has not been addressed as a solution for reducing suppliers.

MITRE and the National Security Agency cooperatively developed and maintained a D3FEND knowledge graph (KG). It provides concepts as an entity from the cybersecurity countermeasure domain, such as dynamic, emulated and file analysis. Those entities are linked by applying relationships such as analyze, may_contains and encrypt. A fundamental challenge for collaborative designers is to encode knowledge and efficiently interrelate the cyber-domain facts generated daily. However, the designers manually update the graph contents with new or missing facts to enrich the knowledge. This paper aims to propose an automated approach to predict the missing facts using the link prediction task, leveraging embedding as representation learning.

D3FEND is available in the resource description framework (RDF) format. In the preprocessing step, the facts in RDF format converted to subject–predicate–object triplet format contain 5,967 entities and 98 relationship types. Progressive distance-based, bilinear and convolutional embedding models are applied to learn the embeddings of entities and relations. This study presents a link prediction task to infer missing facts using learned embeddings.

Experimental results show that the translational model performs well on high-rank results, whereas the bilinear model is superior in capturing the latent semantics of complex relationship types. However, the convolutional model outperforms 44% of the true facts and achieves a 3% improvement in results compared to other models.

Despite the success of embedding models to enrich D3FEND using link prediction under the supervised learning setup, it has some limitations, such as not capturing diversity and hierarchies of relations. The average node degree of D3FEND KG is 16.85, with 12% of entities having a node degree less than 2, especially there are many entities or relations with few or no observed links. This results in sparsity and data imbalance, which affect the model performance even after increasing the embedding vector size. Moreover, KG embedding models consider existing entities and relations and may not incorporate external or contextual information such as textual descriptions, temporal dynamics or domain knowledge, which can enhance the link prediction performance.

Link prediction in the D3FEND KG can benefit cybersecurity countermeasure strategies in several ways, such as it can help to identify gaps or weaknesses in the existing defensive methods and suggest possible ways to improve or augment them; it can help to compare and contrast different defensive methods and understand their trade-offs and synergies; it can help to discover novel or emerging defensive methods by inferring new relations from existing data or external sources; and it can help to generate recommendations or guidance for selecting or deploying appropriate defensive methods based on the characteristics and objectives of the system or network.

The representation learning approach helps to reduce incompleteness using a link prediction that infers possible missing facts by using the existing entities and relations of D3FEND.

The purpose of this paper is to systematically assess the empirical support for central relationships in the empirical literature on foreign market entry mode. The reviewing method overcomes methodological limitations in past reviews.

This review provides a systematic assessment of empirical support through a simple quantitative procedure using transparent criteria for article selection. In total, 1,217 statistical tests from 119 studies published in 44 different scientific journals in the period 1997-2013 are examined across a range of dimensions.

Findings question the frequent use of commonly used measures (e.g. advertising intensity) and control variables (e.g. firm size) and suggest that statements about the importance of mode choice for subsidiary performance may be premature. Methodologically, this study identifies critical issues with regard to interpretation of interactions and the entry mode choice set.

This study limits itself to study the direction of relationships and does not analyze effect sizes. Further, future research may benefit from broadening the entry mode choice by extending the use of multiple outcome models as well as implementing the correct interpretational tools when investigating interactions.

The review is relevant to researchers seeking an overview over the research literature or practitioners interested in the link between mode choice and subsidiary performance.