Search results

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.

This study attempts to discover effective strategies for mobile commerce applications (apps) to grow their consumer base by releasing app strategic updates. Drawing on the landscape search model from strategy research, this study conceptualizes mobile app update strategy as three interdependent decisions, i.e. what business elements are changed in an app strategic update, how substantial the changes are and when strategic updates are released relative to the competitive environment.

Using a field data set of 1,500 strategic updates of seven rival apps in the mobile travel market, this study integrated fuzzy set qualitative comparative analysis (fsQCA) with econometric analysis to analyze how app strategic update decisions interdependently influence app performance.

This study identified three effective and one ineffective mobile app update strategies from the mixed-method analysis, which verified the complex interdependency of app strategic update decisions. A general takeaway from these strategies is that a complex strategy problem on the mobile platform must be solved with respect to the constraints and capabilities of mobile technology.

This study moves beyond a linear view of the relationship between app update frequency and app performance and provides a holistic view of how and why app strategic update decisions mutually influence one another in their impact on app performance. This work makes contributions by identifying interdependency as a conceptual bridge between strategy and mobile app literature and developing an empirically testable version of the landscape search model.

Different information sharing mechanisms and online platform information sharing to different charging models are compared and analyzed.

This paper uses the Stackelberg game model to study the demand information sharing and pricing decisions.

The results show that: (1) the retailer's pricing strategy is the highest when both of them obtain information, while the manufacturer's pricing strategy is affected by the related attributes of different products, such as the sensitivity of consumers to product prices; (2) in the online platform sales model, the demand information data sharing owned by the online platform can bring more expected profits to the whole supply chain and the members of the supply chain, and the higher the accuracy of the information, the higher the expected profit; (3) when the cost of obtaining demand information is zero, that is, the online platform shares the information data about market demand free of charge, the retailer and manufacturer tend to obtain information; (4) for the online platform, charging a certain fee can achieve higher expected profits than free sharing.

Based on the single platform online sales model, this paper uses the Stackelberg game model to study the demand information sharing and pricing decision of a manufacturer and a retailer selling products through the same online platform.

Showrooming presents a complex and evolving challenge to retail managers, as it signifies the emergence of new forms of exchange rules. The purpose of this research is to investigate how factors responsible for information search and evaluation affect showrooming and also consider the consumer mindset as a moderator.

This research undertakes three experimental designs to investigate how the push (i.e. assortment size), pull (i.e. price discount), and mooring (i.e. sunk cost) factors influence consumers' showrooming intention. Specifically, consumers' maximizing tendency plays the role of moderator.

The results reveal that push, pull, and mooring factors are significantly related to consumers' showrooming intention. Furthermore, the findings show that maximizers have higher showrooming intention than satisficers in the context of the push, pull, and mooring factors.

By integrating the push-pull-mooring framework and the maximizing mindset theory, this research proposes a novel research model and the empirical testing results support six hypotheses. The findings add to the body of knowledge in showrooming behavior by taking consumer mindset into account. The results also provide implications for practitioners to develop their retail strategies.

Recently, autonomous vehicles (AV) acceptance has been studied intensively. This paper aims to map and analyze the bibliometric characteristics of AV acceptance literature. Furthermore, this research aims to identify research gaps and propose future research opportunities.

The bibliometric analysis was performed. Scopus database was used as the source of the literature. This study selected and analyzed 297 AV acceptance papers. The performance and science mapping analysis were performed.

The developed countries tended to dominate the topic. The publication outlet tended to be in transportation or technology journals. There were four research themes in existing literature. Technology acceptance model (TAM) and UTAUT2 tended to be used for explaining AV acceptance. AV acceptance studies tended to use two types of psychological concepts for understanding AV acceptance, namely risk related concepts and functional utilitarian benefit related concepts. In the context of research design, quantitative approach tended to be used. Self-driving feature was the most exploited feature of AV in the existing literature. Three research gaps were mapped and future research opportunities were proposed.

This paper provided a comprehensive information that allowed scientists to develop future research on AV acceptance.

There is lack of paper that discussed the bibliometric characteristics of AV acceptance literature. This paper fulfilled the gap.

The ongoing paradigm shift in the energy sector holds paramount implications for the realization of the sustainable development goals, encompassing critical domains such as resource optimization, environmental stewardship and workforce opportunities. Concurrently, this transformative trajectory within the power sector possesses a dual-edged nature; it may ameliorate certain challenges while accentuating others. In light of the burgeoning research stream on open innovation, this study aims to examine the intricate dynamics of knowledge-based industry-university-research networking, with an overarching objective to elucidate and calibrate the equilibrium of ambidextrous innovation within power systems.

The authors scrutinize the role of different innovation organizations in three innovation models: ambidextrous, exploitative and exploratory, and use a multiobjective decision analysis method-entropy weight TOPSIS. The research was conducted within the sphere of the power industry, and the authors mined data from the widely used PatSnap database.

Results show that the breadth of knowledge search and the strength of an organization’s direct relationships are crucial for ambidextrous innovation, with research institutions having the highest impact. In contrast, for exploitative innovation, depth of knowledge search, the number of R&D patents and the number of innovative products are paramount, with universities playing the most significant role. For exploratory innovation, the depth of knowledge search and the quality of two-mode network relations are vital, with research institutions yielding the best effect. Regional analysis reveals Beijing as the primary hub for ambidextrous and exploratory innovation organizations, while Jiangsu leads for exploitative innovation.

The study offers valuable implications to cope with the dynamic state of ambidextrous innovation performance of the entire power system. In light of the findings, the dynamic state of ambidextrous innovation performance within the power system can be adeptly managed. By emphasizing a balance between exploratory and exploitative strategies, stakeholders are better positioned to respond to evolving challenges and opportunities. Thus, the study offers pivotal guidance to ensure sustained adaptability and growth in the power sector’s innovation landscape.

The primary originality is to extend and refine the theoretical understanding of ambidextrous innovation within power systems. By integrating several theoretical frameworks, including social network theory, knowledge-based theory and resource-based theory, the authors enrich the theoretical landscape of power system ambidextrous innovation. Also, this inclusive examination of two-mode network structures, including the interplay between knowledge and cooperation networks, unveils the intricate interdependencies between these networks and the ambidextrous innovation of power systems. This approach significantly widens the theoretical parameters of innovation network research.

Following the theory of emotional events, this paper aims to use the bright triad and the dark tetrad as representations to investigate the role of positive and negative personality patterns in achieving positive and negative innovation. The study also examines the mediating role of emotional intelligence and abusive supervision and the interactive role of emotional exhaustion in understanding the relationship between positive and negative personality patterns and positive and negative innovation.

To test the hypotheses of the study model, a set of questionnaires was distributed to a sample of 500 medical officers working in different departments of public hospitals in southern Iraq. The data were analysed using the structured equation model.

The results of the current study confirm previous studies on emotional intelligence because the bright triad negatively associates with negative innovation and positively associates with positive innovation. Meanwhile, the dark tetrad positively associates with negative innovation through abusive supervision, and that emotional exhaustion reinforces the negative side and weakens the positive side of the relationships.

This study contributes to the literature by emphasising that the values represented by the bright triad have a strong readiness to show positive innovation and immunity to negative influence caused by abusive supervision. Meanwhile, the negative emotions of the dark tetrad pattern result in negative patterns because they correlate with negative innovation and the avoidance of positive behaviour, which is escalated by abusive supervision.

The purpose of this paper is to develop a comprehensive overview of green innovation (GI) in China, which is carried out by reviewing the evolution of GI from 2000 to 2019, and the main type of technology, actors and localizations. When appropriate, GI is compared to non-GI.

The study uses patent data from the European Patent Office database (PATSTAT); these data are processed to map trends and identify the main contributors to GI and the location of such innovation. The findings are then discussed and complemented with academic literature.

Key findings reveal an increasing divergence between GI and nongreen innovation after the 2008 crisis. It is also observed that solar energy appears to be the main component of GI in China, with a shift from photovoltaic thermal energy to solar photovoltaic energy after 2008. Other areas, such as waste management, greenhouse gases capture and climate change adaptation, are less innovative. Companies play an essential role in the development of all types of innovation. In terms of location, green patents are mainly filed in China’s three main megacities. The study also highlights the significant role of the Chinese state, which led policies shaping the trajectories and forms of GI.

This study expands knowledge on GI in China, highlighting its main specificities and the role of key actors. It provides to the reader a comprehensive picture of China’s green policies and innovation realities. The results can therefore be used to improve the understanding of GI evolution in China and facilitate the formulation of new research questions.

User acceptance is a necessary precondition to implementing self-driving buses as a solution to public transport challenges. Focusing on potential users in a real-life setting, this paper aims to analyze the factors that affect their willingness to use public autonomous shuttles (PASs) as well as their word-of-mouth (WOM) intentions.

Grounded on Unified Theory of Acceptance and Use of Technology (UTAUT2), the study was carried out on a sample of 318 potential users in a real-life setting. The hypothesized relationships were tested using partial least squares structural equation modeling (PLS-SEM).

The study reveals that performance expectancy, facilitating conditions, hedonic motivation and trust are significant predictors of PAS usage intention, which is, in turn, related to WOM communication. Additionally, the factors that impact the intention to use a PAS are found to exert an indirect effect on WOM, mediated by usage intention.

This study includes practical insights for transport decision-makers on PAS service design, marketing campaigns and WOM monitoring.

While extant research focuses on passengers who have tried autonomous shuttles in experimental settings, this article adopts the perspective of potential users who have no previous experience with these vehicles and identifies the link between usage intention and WOM communication in a real-life traffic environment.

若要引入自動駕駛巴士來解決公共交通的問題和挑戰,一個必不可少的先決條件是得到用戶的認可。本研究透過重點分析活在真實生活環境中的潛在用戶,來探討影響他們使用公共自動交通工具的意願和口碑動機的各個因素。

本研究以延伸整合型科技接受模式為基礎,對一個涵蓋處身於真實生活環境中318名潛在用戶的樣本進行分析和探討。研究人員以偏最小平方法的結構方程模型 (PLS-SEM), 去測試各個被假設的關聯。

研究結果顯示,績效期望、有利條件、享樂動機和信任均明顯能夠預測人們使用公共自動交通工具的意願,而人們使用公共自動交通工具的意願又反過來與口碑溝通有所相關。另外,研究人員發現,影響人們使用公共自動交通工具意願的各個因素,對口碑會產生間接的影響,而使用意願是會起著調節作用的。

現存的學術研究均聚焦分析那些曾於實驗設置下坐過自動交通工具的人士,而本研究卻採用從未坐過自動交通工具人士的角度來進行分析與探討,並且找出了於實際的交通環境裡、使用意願與口碑溝通之間的關聯。

本研究提供的啟示,對有關公共自動交通工具服務設計、市場營銷活動和口碑監督工作的運輸決策者來說頗具實務意義。

This study aims to investigate the micro mechanism of macro rheological characteristics for composite modified asphalt.Grey relational analysis (GRA) was used to analyze the correlation between macro rheological indexes and micro infrared spectroscopy indexes.

First, a dynamic shear rheometer and a bending beam rheometer were used to obtain the evaluation indexes of high- and low-temperature rheological characteristics for asphalt (virgin, SBS/styrene butadiene rubber [SBR], SBS/rubber and SBR/rubber) respectively, and its variation rules were analyzed. Subsequently, the infrared spectroscopy test was used to obtain the micro rheological characteristics of asphalt, which were qualitatively and quantitatively analyzed, and its variation rules were analyzed. Finally, with the help of GRA, the macro-micro evaluation indexes were correlated, and the improvement efficiency of composite modifiers on asphalt was explored from rheological characteristics.

It was found that the deformation resistance and aging resistance of SBS/rubber composite modified asphalt are relatively good, and the modification effect of composite modifier and virgin asphalt is realized through physical combination, and the rheological characteristics change with the accumulation of functional groups. The correlation between macro rutting factor and micro functional group index is high, and the relationship between macro Burgers model parameters and micro functional group index is also close.

Results reveal the basic principle of inherent-improved synergistic effect for composite modifiers on asphalt and provide a theoretical basis for improving the composite modified asphalt.