Kybernetes最新文献

Purpose

Technological tools for knowledge management (KM) actively support and enhance knowledge acquisition and sharing in organizations. However, technology for KM has been understudied, especially in terms of disruptive technologies (DTs). There is a need to identify how DTs, which are becoming increasingly important in industry and society, are applied to KM and their impact. This paper aims to examine the current state of technology and DT adoption in KM.

Design/methodology/approach

The analysis involves four steps. First, we examine the current status of DT in academia through a keyword co-occurrence network of literature. Second, we analyze the technological convergence (TC) of KM technology through the cooperative patent classification code co-classification analysis of patents. Third, we explore the main topics of KM technologies using BERTopic, and finally, we explore the introduction of DT into KM technologies and suggest potential TC combinations for the future.

Findings

KM technologies can be categorized into four main topics (knowledge acquisition, sharing, searching, and transfer), and DT is most often applied to knowledge transfer and acquisition. The DTs that are attracting attention from academia and industry are artificial intelligence, augmented and virtual reality, and blockchain, which have applications in healthcare, supply chain management, and human resource management.

Originality/value

The findings provide useful insights for organizations to build a technology roadmap for KM. They can also improve the rigid mindset of organization employees toward DT adoption and innovation. By adopting a KM system that leverages DT, organizations will be able to manage and operate efficiently and systematically.

Purpose

This study aims to enhance an enterprise’s private cloud services by optimally determining the ownership of cloud computing resources and responsibility for maintenance and operations. The core objective is to identify the most cost-effective private cloud deployment model at the intersection of technology and business considerations.

Design/methodology/approach

This study evaluates three ownership and responsibility models, each encompassing decisions related to candidate data center locations, resource provisioning, and demand placements. Drawing from the cloud computing literature, these models are referred to as deployment models. The research formulates a private cloud deployment model selection problem and introduces an established Lagrangian-relaxation-based optimization approach, combined with a novel greedy relieving-pooling heuristic, to facilitate model selection.

Findings

This study identifies the optimal deployment model for a representative instance using real test-bed data from the US, demonstrating the private cloud deployment model selection problem. Various numerical examples are analyzed to explore the influence of environmental parameters. Generally, the virtual PC model is optimal for low demand arrival rates and resource requirements, while the on-premises PC model is preferable for higher values of these parameters. Additionally, the virtual PC model is found to be optimal when enroute latency coefficients are large.

Originality/value

This study contributes to the literature by formulating an optimization problem that integrates performance, financial, and assurance metrics for enterprises. The introduction of a solution approach enables enterprises to make informed decisions regarding ownership and responsibility design. The study effectively bridges the gap between academic research and industry demands from a business perspective.

Purpose

This study aims to explore the potential role of supply chain digital transformation on collaborative knowledge creation, supply chain innovation, and value co-creation in new norms. It also examines the impact of collaborative knowledge creation and supply chain innovation on value co-creation. Furthermore, the study examines the impact of collaborative knowledge creation on supply chain innovation. Finally, it investigates the possible mediating role of knowledge absorptive capacity and relationship quality in shaping these interactions.

Design/methodology/approach

To establish the empirical part of this study, the collection of data involved distributing a questionnaire to 247 managers working in manufacturing companies. The measurement model assessment and hypothesis testing were performed employing the PLS-SEM approach.

Findings

The findings indicate that supply chain digital transformation significantly impacts collaborative knowledge creation, supply chain innovation, and value co-creation. This study also confirms the significant impact of collaborative knowledge creation on supply chain innovation and value co-creation. Furthermore, it reveals that knowledge absorptive capacity mediates the impact of supply chain digital transformation on collaborative knowledge creation. It also shows that the impact of collaborative knowledge creation on supply chain innovation and value co-creation is mediated by relationship quality among participants.

Originality/value

The findings of this study make significant contributions to academic theory, existing literature, and the scholarly community within the realms of supply chain management, innovation, knowledge management, and value co-creation. It also offers practical implications for managers to strategically navigate the evolving norms of supply chain management. Companies can use these insights to improve their innovation processes and knowledge management, while policymakers can consider the study's findings when developing supportive frameworks for the manufacturing sector.

Purpose

This paper studies the location-inventory problem (LIP) in pallet pooling systems to improve resource utilization and save logistics costs, which is a new extension of the classical LIP and also an application of the LIP in pallet pooling systems.

Design/methodology/approach

A mixed-integer linear programming is established, considering the location problem of pallet pooling centers (PPCs) with multi-level capacity, multi-period inventory management and bi-directional logistics. Owing to the computational complexity of the problem, a hybrid genetic algorithm (GA) is then proposed, where three local searching strategies are designed to improve the problem-solving efficiency. Lastly, numerical experiments are carried out to validate the feasibility of the established model and the efficiency of the proposed algorithm.

Findings

The results of numerical experiments show that (1) the proposed model can obtain the integrated optimal solution of the location problem and inventory management, which is better than the two-stage model and the model with single-level capacity; (2) the total cost and network structure are sensitive to the number of PPCs, the unit inventory cost, the proportion of repairable pallets and the fixed transportation cost and (3) the proposed hybrid GA shows good performance in terms of solution quality and computational time.

Originality/value

The established model extends the classical LIP by considering more practical factors, and the proposed algorithm provides support for solving large-scale problems. In addition, this study can also offer valuable decision support for managers in pallet pooling systems.

Purpose

In this study, a conceptual model was developed and analyzed to test the mediating role of positive psychological capital (PPC) in the impact of organizational support perceived by employees who continue their professional lives in the port sector, which is an important sub-branch of the maritime sector, on employee performance (EP).

Design/methodology/approach

The data for the analysis of the model in question were collected through a survey method from employees in the work site and units of 14 port enterprises in the Eastern Mediterranean region of Türkiye. A total of 406 usable data were analyzed with the SmartPLS 4 analysis program.

Findings

The analysis did not confirm the significant positive effect of perceived organizational support (POS) on EP. On the other hand, the analysis found that POS had a significant positive impact on PPC. Likewise, the significant positive effect of PPC on EP was confirmed. The analysis also concluded that PPC was the full mediator variable in the impact of POS on EP.

Practical implications

This study helps managers find out how they can improve employees' EP with qualified POS and PPC.

Originality/value

The current study reveals the role of PPC in the mechanism underlying the controversial relationship between POS and EP and, thus, contributes significantly to both literature and practice.

Purpose

Conventional approaches such as Data Envelopment Analysis (DEA) and Fuzzy Data Envelopment Analysis (FDEA) cannot effectively account for uncertainty, which can lead to imprecise decision-making. Furthermore, these methods frequently rely on precise numbers, ignoring the inherent uncertainty of real-world data. To address this gap, the research question arises: How can we develop a methodology that combines Z-number theory and FDEA to provide a comprehensive assessment of residency preferences in European countries while accounting for uncertainty in information reliability? The proposed methodology aims to fill this gap by incorporating Z-number theory and FDEA.

Design/methodology/approach

The proposed study assesses residency preferences across 39 European countries, focusing on key factors like environment, sustainability, technology, education, and development, which significantly influence individuals' residency choices. Unlike conventional DEA and FDEA approaches, the proposed method introduces a novel consideration: dependability. This inclusion aims to refine decision-making precision by accounting for uncertainties related to data reliability. The proposed methodology utilizes an interval approach, specifically employing the a-cut approach with interval values in the second step. Unlike using crisp values, this interval programming resolves formulations to determine the efficiencies of decision-making units (DMUs).

Findings

The comprehensive findings provide valuable insights into the distinctive factors of European nations, aiding informed decision-making for residency choices. Malta (75.6%-76.1%-75.8%), Austria (78.2%-78%-76.1%), and the United Kingdom (79.3%-78.4%-77%) stand out with distinct characteristics at levels of a = 0-a = 0.5-a = 1, assuming the independence of variables of the overall evaluation. Individual consideration of each factor reveals various countries as prominent contenders, except for the environmental factor, which remains consistent across countries.

Originality/value

Traditional DEA models encounter challenges when dealing with uncertainties and inaccuracies, particularly in the evaluation of large systems. To overcome these limitations, we propose integrating Z-numbers—a powerful mathematical tool for modeling uncertainty—into the conventional DEA process. Our methodology not only assesses the effectiveness of countries across various socio-economic and environmental metrics but also explicitly addresses the inherent uncertainties associated with the data. By doing so, it aims to enhance the precision of decision-making and provide valuable insights for policymakers and stakeholders.

Purpose

Knowledge sharing is critical to creating value in platform ecosystems. However, participants refrain from sharing knowledge and even engage in free-riding behavior, thereby causing the value co-destruction of the platform ecosystems. To encourage knowledge sharing among participants, it is essential to analyze the influencing factors and decision-making mechanisms of knowledge sharing in the platform ecosystems.

Design/methodology/approach

The study investigated the issue of knowledge sharing among participants in platform ecosystems, based on the stochastic differential game model. Considering the uncertain factors, the Nash non-cooperative game, Stackelberg leader-follower game, and cooperative game models were proposed. By utilizing system dynamics and numerical simulations, the key influencing factors and mechanisms of knowledge sharing were deeply explored, consequently providing game solutions to achieve the Pareto optimality of the ecosystem.

Findings

Participants' innovation capability and the marginal benefits of knowledge-sharing positively impact knowledge-sharing decisions, while the environmental knowledge decay rate has a negative influence. The platform subsidy mode enhances the knowledge-sharing effect, and the collaborative cooperation mode can realize the Pareto optimization of the system.

Practical implications

The research findings will provide theoretical support for fostering knowledge innovation and sustainable development of platform ecosystems. Managers should cultivate an innovative environment, establish fair reward mechanisms, and utilize subsidies to promote knowledge sharing, leading to higher value creation.

Originality/value

Utilizing the stochastic differential game model, the study proposed various game-theoretic frameworks to analyze participants' knowledge-sharing strategies. The integration of system dynamics and numerical simulations provides a practical approach to understanding the key influencing factors and decision-making processes.

Purpose

This study investigates advertising avoidance behavior among consumers, specifically in the realm of meta-platforms. It explores the impacts of digital burnout, advertising clutter, perceived advertising risk, and goal impediment on cognitive and behavioral ad avoidance.

Design/methodology/approach

With a sample of 410 respondents, the research employs a comprehensive analysis approach with SEM and CFA, integrating Avoidance Motivation Theory. It examines direct and indirect influences on ad avoidance, mediated by consumer emotions and attitudes. The study highlights the moderating role of content quality in shaping these relationships.

Findings

Significant links were found between digital burnout, clutter, perceived advertising risk, and goal impediment with cognitive and behavioral ad avoidance. The study emphasizes the importance of content quality and suggests strategies that focus on emotional resonance, user alignment, and reduced intrusion.

Practical implications

For advertisers and marketers in digital spaces, the findings recommend strategies promoting healthy technology usage, streamlined advertising content, transparent communication aligned with user goals, and emotionally resonant campaigns to mitigate ad avoidance behaviors.

Social implications

Understanding consumer sentiments aids policymakers in creating conducive advertising models, benefiting both consumers and businesses. This enhances user experiences in digital environments.

Originality/value

The paper distinctively applies the Avoidance Motivation Theory to the context of avoiding social media advertisements, thereby uncovering the causes of negative consumer emotions and attitudes, and highlighting the crucial role of content quality as a means to counteract these adverse reactions.

Purpose

Social entrepreneurship is a topical issue in the context of entrepreneurial intention. Our quantitative study seeks to explore the complex and dynamic nexus of the ever-evolving landscape of entrepreneurial intentions, which results in socioeconomic development through the mediating influence of entrepreneurial knowledge.

Design/methodology/approach

The South Asian region was considered a research population, considering its characteristics and inclination toward social entrepreneurial activities. The required data were collected using an online survey questionnaire. 330 questionnaires were mailed online to the targeted participants, and 239 responses were received and analyzed using SPSS and AMOS software.

Findings

The study found a significant positive relationship between entrepreneurial intention and socioeconomic development. A 1% improvement in entrepreneurial intention corresponds to a 40% increase in socioeconomic development and 17% enhancement in entrepreneurial knowledge. Our study also demonstrates that a 1% improvement in entrepreneurial intention brings about a substantial improvement of 26% in socioeconomic development when mediated by entrepreneurial knowledge.

Research limitations/implications

It is recommended that intentional learning spaces focus on intensifying social entrepreneurial intention and develop mechanisms for knowledge transfer platforms to facilitate knowledge sharing among social entrepreneurs. Organizations may support and take initiatives to bridge the gap between experienced and novice social entrepreneurs. Institutions may introduce incentive structures that promote sustainable entrepreneurship, highlight social entrepreneurs’ success stories, and emphasize the linkage between intention, knowledge, and positive societal outcomes.

Originality/value

Owing to the lack of literature and inadequate empirical research, our study was articulated to enhance existing knowledge and postulate the basis for high-order empirical studies in the context of social entrepreneurial intention backed by entrepreneurial knowledge. Moreover, this study provoked entrepreneurial intention based on the theory of planned behavior with the mediating influence of entrepreneurial knowledge, which adds a distinctive dimension to social entrepreneurial intention, enhances research originality, and provides practical implications for individuals seeking to thrive in dynamic environments.