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Existing studies have paid less attention to the impact of knowledge accumulation on digital transformation and its boundary conditions. Hence, this study aims to investigate the effects of ambidextrous knowledge accumulation on manufacturing digital transformation under the moderation of dynamic capability.

This study divides knowledge accumulation into exploratory and exploitative knowledge accumulation and divides dynamic capability into alliance management capability and new product development capability. To clarify the relationship among ambidextrous knowledge accumulation, dynamic capability and manufacturing digital transformation, the authors collect data from 421 Chinese listed manufacturing enterprises from 2016 to 2020 and perform analysis by multiple hierarchical regression method, heterogeneity test and robustness analysis.

The empirical results show that both exploratory and exploitative knowledge accumulation can significantly promote manufacturing digital transformation. Keeping ambidextrous knowledge accumulation in parallel is more conducive than keeping single-dimensional knowledge accumulation. Besides, dynamic capability positively moderates the relationship between ambidextrous knowledge accumulation and manufacturing digital transformation. Moreover, the heterogeneity test shows that the impact of ambidextrous knowledge accumulation and dynamic capabilities on manufacturing digital transformation varies widely across different industry segments or different regions.

First, this paper shifts attention to the role of ambidextrous knowledge accumulation in manufacturing digital transformation and expands the connotation and extension of knowledge accumulation. Second, this study reveals that dynamic capability is a vital driver of digital transformation, which corroborates the previous findings of dynamic capability as an important driver and contributes to enriching the knowledge management literature. Third, this paper provides a comprehensive micro measurement of ambidextrous knowledge accumulation and digital transformation based on the development characteristics of the digital economy era, which provides a theoretical basis for subsequent research.

Practical needs in geographical information systems (GIS) have led to the investigation of formal, sound and computational methods for spatial analysis. Since models based on topology of R² have a serious problem of incapability of being applied directly for practical computations, we have noticed that models developed on the raster space can overcome this problem. Because some models based on vector spaces have been effectively used in practical applications, we then introduce the idea of using the raster space as our platform to study spatial entities of vector spaces. In this paper, we use raster spaces to study not only morphological changes of spatial entities of vector spaces, but also equal relations and connectedness of spatial entities of vector spaces. Based on the discovery that all these concepts contain relativity, we then introduce several new concepts, such as observable equivalence, strong connectedness, and weak connectedness. Additionally, we present a possible method of employing raster spaces to study spatial relations of spatial entities of vector spaces. Since the traditional raster spaces could not be used directly, we first construct a new model, called pansystems model, for the concept of raster spaces, then develop a procedure to convert a representation of a spatial entity in vector spaces to that of the spatial entity in a raster space. Such conversions are called approximation mappings.

The study of spatial entities needs a model that is not only fully observable and controllable, but also computable. Euclidean topology on R² is a usually used tool for this study, but it has the following two weaknesses. First, there exists some phenomenon of human perception of the spatial entity that cannot be simulated by it. Second, its observation of the basic geometric properties (interior, exterior, boundary) of the spatial entity lacks computability so that the model based on it lacks computability and cannot be directly used to practical systems. Consequently, in this paper, we present another tool for studying spatial entities – raster quasi‐topology on R² and then compare the two tools.

Social commerce using social media has been on the rapid increase. Among various social commerce models, group-buying has become the mainstream. There is a paucity of research related to how customers perceive value in group-buying situations. This paper aims to examine and analyze various factors that influence perceived customer value in group-buying.

Data were collected using a survey on customers who had purchased a restaurant service deal on a group-buying site. A partial least squares technique was used to estimate the model.

Results show that perceived customer value affects customers’ group buying intentions and that all four antecedents of perceived value (low price, valence of experience, trust in social media and reputation of the group-buying site) have a significant influence. Implications and further research directions are discussed at the end of the paper.

This study provides valuable strategic implications for social commerce firms.

Key core technology is the most important weapon of the country, and breaking through the “strangled” problem is one of the real problems that China’s emerging industries and enterprises must solve. Accurately identifying the “strangled” problem will help China accelerate the realization of high-level scientific and technological self-reliance and win the battle against key core technologies.

Combined with the characteristics of key core technologies, the key core technology evaluation system was constructed from four dimensions: technology innovation, technology radiation, technology economy and technology safety. We adopt the entropy TOPSIS method to evaluate the patents, and the patents with the top 5% scores are identified as key core technology patents. Then, this study identifies key core technology “strangled” problems in three dimensions: technology value advantage, competitive advantage and quantitative advantage.

Taking the patent data of the global new generation information technology industry from 2011 to 2023 as a sample, 178 moderately “strangled” technologies and 49 severely “strangled” technologies are selected. The study results are consistent with the current situation of the new generation information technology industry’s development, and verify the feasibility and reliability of the key core technology “strangled” problem identification model.

This study uses patent data to identify key core technologies and “Strangled” in the new generation information technology industry. It can provide a reference for relevant national departments and agencies, as well as universities and enterprises.

The purpose of this study is to address the critical need for patent value evaluation within patent management, particularly in the context of the digital economy. Recognizing the importance of utilizing historical data, this research aims to uncover effective methodologies that enhance the appraisal of patent value, which is vital for informed decision-making in the management of scientific and technological advancements.

This study introduces a comprehensive evaluation model by analyzing various factors that influence patent value. An index system is constructed that integrates technical, economic and legal aspects to facilitate a nuanced assessment of patents. The methodological core of this research is the development of an XGBoost patent value appraisal model, which incorporates Bayesian optimization to refine the evaluation process. The model’s validity is tested through empirical analysis of patents in the rapidly evolving sector of cloud computing.

The empirical results demonstrate that the XGBoost model, strengthened by Bayesian optimization, outperforms traditional categorization techniques. The proposed model shows superior performance in terms of accuracy, precision, recall rate and operational feasibility. These findings indicate a significant improvement in the precision of patent potential and value assessments, leading to more reliable and actionable insights for patent management.

This study introduces a novel patent evaluation model that combines XGBoost with Bayesian optimization. XGBoost enhances performance by integrating weak learners, ideal for complex, nonlinear problems like patent valuation. Bayesian optimization refines hyperparameters efficiently using prior distributions and known results. Its practical implications for patent management and technology exploration are substantial, offering a new tool for strategic decision-making.

Well-constructed transportation infrastructure may effectively decrease barriers to the flow of innovative human resources and inventive elements, accelerating enterprise innovation activities. This study will explore how HSR helps enterprises achieve ambidextrous innovation, including the mediating mechanism of absorbed slack resources, innovative talents, and the heterogeneous effects of management shareholding ratio and financing constraints.

Based on resource dependence theory and social network theory, this study employs a quasi-natural experiment of China’s high-speed railway and builds a multi-time point DID model to investigate its influence on enterprise ambidextrous innovation.

Results suggest that the HSR positively influences both exploitative and exploratory innovation, and the influence is more substantial on exploitative innovation. Further analysis finds two influencing channels through which HSR influences enterprise ambidextrous innovation: providing redundant resources and attracting innovative talents. Heterogeneity analysis indicates that HSR has a more significant positive effect on exploratory innovation for enterprises with high management shareholding. In the low financing constraint group, the HSR opening has a more significant impact on ambidextrous innovation.

In ambidextrous innovation, enterprises should rationalize the allocation of resources, attach importance to the innovative talent introduction, and choose differentiated paths based on intrinsic characteristics. Meanwhile, the government should actively improve the HSR routes and continuously improve the innovative environment.

This study enriches the theoretical research framework of HSR and ambidextrous innovation by identifying the channel mechanisms and boundary conditions through which HSR affects ambidextrous innovation and expands the consequences of HSR and the antecedents of ambidextrous.

The purpose of this study is to explore how digital construction policy (DCP) drives enterprise green innovation (EGI) from an information processing theory (IPT) perspective, including the mediating mechanisms of market information accessibility and operational risk, the moderating role of intellectual property protection (IPP) and product market competition (PMC) and the heterogeneous effects of ownership, Internet development and managerial ability.

Based on the matched panel data of A-share listed enterprises from 2011 to 2019 and the Broadband China policy as a quasinatural experiment, this study investigates the impact of DCP on EGI by constructing a multi-time point difference-indifferences (DID) model.

Digital construction policies can significantly promote EGI. DCP works in two fundamental ways, namely by increasing market information accessibility and reducing operational risk. IPP and PMC significantly increased the contribution of digital construction policies to EGI. Heterogeneity analysis found that digital technology has a stronger promotion effect for SOEs, high-managerial-ability enterprises and enterprises in regions with low Internet development levels.

The study provides new insights about the antecedents of EGI from a DCP perspective. It also enlightens emerging economies to actualize green innovation under the digital wave.

From the perspective of IPT, this study explains the mechanism of DCP-driven EGI. It enhances understanding of the relationship between DCP and EGI.

The study focuses on how to build long-term relationships with multi-channel agencies (MCAs) (dealers) who serve multiple manufacturers on a non-exclusive basis in a business-to-business (B2B) market. This study looks at the framework of relational benefits-commitment-long term orientation in a business-to-business context.

Data were collected from MCAs of three leading companies in the food distribution business. The survey used established scales to measure the relational benefits (core, operational, social and special treatment), commitment (affective and calculative) and long-term orientation (LTO).

The findings of the study show that core, social and special treatment benefits influence calculative commitment, and operational and special treatment benefits influence affective commitment. The study also supports that calculative and affective commitment play an important role in understanding the loyalty of MCAs.

The research examines how relational benefits impact commitment and loyalty among MCAs and manufacturers, in a non-exclusive relationship, in the business-to-business environment. This study incorporates social exchange theory (SET), relational benefits paradigm and commitment and long-term orientation in its framework and tests it within the food distribution industry. This study is the first of its kind to examine the effects of relational benefits on MCAs behavior in a food supplier–buyer setting.

Hotels conducting international business are acknowledging the importance of an expatriate general manager (GM), to increase the effectiveness of their knowledge management system through the sharing of knowledge between expatriates and local employees. In the aspect of comparative leadership studies, this study attempts to compare and analyze the effects of knowledge sharing (KS) efforts, which are competencies of expatriate GMs and local GMs, on employee trust, organizational KS and employee loyalty.

Data were collected from employees of 7 hotels managed by expatriate GMs among 16 franchising luxury (5-star) hotels, and from employees of 6 hotels operated by local GMs among 9 local luxury hotels located in Korea. Structural equation modeling method using SmartPLS 3.3.3 was used to analyze the data.

Expatriate GM’s two-way KS influences affective trust but does not influence cognitive trust. Affective trust influences cognitive and organizational KS but does not influence employee loyalty. Cognitive trust does not influence organizational KS but influences employee loyalty. Finally, organizational KS significantly affects employee loyalty. In addition, in the analysis comparing the estimates between expatriate and local GM group, significant differences in groups were found for the impact of GM’s two-way KS on cognitive trust, for the impact of affective trust on organizational KS, for the impact of affective trust on employee loyalty and for the impact of cognitive trust on organizational KS.

This study shows that knowledge management designs need to consider different effects of expatriate GMs’ and local GMs’ capabilities on employee attitudes and behavior considering cultural impacts. Expatriate GMs will greatly benefit their effort for KS by assuring employees that they are attentive to their needs, interests and problems.

This study not only contributes to the existing social capital theory but also provides managerial implications for human resources management in the hospitality field through a comparative study of KS efforts of expatriate and local GMs.