Kybernetes最新文献

Purpose

Interdisciplinary inquiry has been increasingly adopted to address issues of growing complexity in the biophysical and social sciences, as for example in agricultural research and rural development. The purpose of this article is to trace the origins of a Postgraduate Programme in Agroecosystems (PGA) in Brazil in order to discuss how its interdisciplinary practices have been enacted and epistemologically and institutionally constrained in just over 25 years of teaching and research activities.

Design/methodology/approach

Conceptualized as a systemic inquiry, the study reported here builds upon participant observation, empirical evidence and literature-based analysis.

Findings

Some of the academic features of the PGA introduced to facilitate interdisciplinary integration are presented and discussed, as well as their main challenges and obstacles, notably those emerging from “disciplinary imperialism” hindering individuals to work towards interdisciplinary inquiry and collaborative learning.

Originality/value

Raising epistemological awareness and building systems literacy are critical aspects to be addressed to foster the embodiment of interdisciplinary inquiry practices. This might also lead to new understandings and to new and productive forms of joint teaching and research practices, fostering interdisciplinary integration.

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

Purpose

Airline self-service technology (SST) has attracted attention from both the academic and aviation sectors. As the use of SST can reduce airlines’ operating costs, investigating SST usage at airports is particularly important for the aviation sector. The extant literature has explored users’ SST usage intention, but users’ switching intentions from traditional manual counter services to SST is still limited. Therefore, to address this issue, we used the push–pull–mooring (PPM) theoretical framework to develop a research model to explore user switching intention.

Design/methodology/approach

We utilized a mixed-methods approach. A qualitative approach (i.e., semistructured interviews) was first employed to recognize and choose the candidate factors. Then, we collected 450 valid responses through an online survey to test the model. The partial least squares method was used for data analysis.

Findings

We found that several push (perceived dissatisfaction and perceived inconvenience), pull (perceived ease of use, perceived usefulness and service process fit), and mooring (personal innovativeness and inertia) factors significantly influence switching intention. Additionally, mooring factors exert contextual effects on the relationships between push and switching intentions and between pull factors and switching intentions.

Originality/value

This study contributes to the literature by further increasing our understanding of user switching intentions regarding SSTs from the PPM perspective and offering guidance for the aviation sector to attract and retain customers.

Purpose

The primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.

Design/methodology/approach

This study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.

Findings

The research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.

Research limitations/implications

Despite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.

Originality/value

The research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

Purpose

In situations where the crew is reduced, the optimization of crew task allocation and sequencing (CTAS) can significantly enhance the operational efficiency of the man-machine system by rationally distributing workload and minimizing task completion time. Existing related studies exhibit a limited consideration of workload distribution and involve the violation of precedence constraints in the solution process. This study proposes a CTAS method to address these issues.

Design/methodology/approach

The method defines visual, auditory, cognitive and psychomotor (VACP) load balancing objectives and integrates them with workload balancing and minimum task completion time to ensure equitable workload distribution and task execution efficiency, and then a multi-objective optimization model for CTAS is constructed. Subsequently, it designs a population initialization strategy and a repair mechanism to maintain sequence feasibility, and utilizes them to improve the non-dominated sorting genetic algorithm III (NSGA-III) for solving the CTAS model.

Findings

The CTAS method is validated through a numerical example involving a mission with a specific type of armored vehicle. The results demonstrate that the method achieves equitable workload distribution by integrating VACP load balancing and workload balancing. Moreover, the improved NSGA-III maintains sequence feasibility and thus reduces computation time.

Originality/value

The study can achieve equitable workload distribution and enhance the search efficiency of the optimal CTAS scheme. It provides a novel perspective for task planners in objective determination and solution methodologies for CTAS.

Purpose

This study examined the reciprocal influence of demand learning and preference matching in the context of store brand customization. The demand-learning effect refers to the collection of market demand information through production, based on pre-order demands, enabling retailers to accurately predict and allocate product quantities, thus improving inventory management. The preference-matching effect involves engaging consumers in the production and design processes of store brands to align fully with their preferences, thereby increasing the purchase impact of store brand products and promoting consumption.

Design/methodology/approach

We employ game-theoretic models to analyze a two-echelon supply chain consisting of a manufacturer and a retailer. The retailer offers both national brands, manufactured by the supplier and in-house store brands. To enhance their competitive edge, the retailer can adopt a customized strategy targeting the store brand to attract a wider consumer base.

Findings

The analysis reveals that, under low commission fees, the manufacturer consistently opts for high production quantities, irrespective of the level of demand uncertainty. However, when the perceived value of a store brand is low and demand uncertainty is either low or high, the retailer should choose a minimal or zero production quantity. The decision-making process is influenced by the customization process, wherein the effects of demand learning and preference matching occasionally mutually reinforce each other. Specifically, when the perceived value of a store brand is low, or the product cost is high, along with high customization costs, the interplay between demand learning and preference matching becomes mutually inhibiting. Consequently, the significance of store brand customization diminishes.

Originality/value

This study enhances the current body of knowledge by providing a deeper understanding of the theoretical value of store brand customization. In addition, it offers valuable decision-making support to enterprises by assisting them in selecting appropriate inventory and customization strategies.

Purpose

As the role of AI on human teams shifts from a tool to a teammate, the implementation of AI teammates into knowledge-intensive crowdsourcing (KI-C) contest teams represents a forward-thinking and feasible solution to improve team performance. Since contest teams are characterized by virtuality, temporality, competitiveness, and skill diversity, the human-AI interaction mechanism underlying conventional teams is no longer applicable. This study empirically analyzes the effects of AI teammate attributes on human team members’ willingness to adopt AI in crowdsourcing contests.

Design/methodology/approach

A questionnaire-based online experiment was designed to perform behavioral data collection. We obtained 206 valid anonymized samples from 28 provinces in China. The Ordinary Least Squares (OLS) model was used to test the proposed hypotheses.

Findings

We find that the transparency and explainability of AI teammates have mediating effects on human team members’ willingness to adopt AI through trust. Due to the different tendencies exhibited by members with regard to three types of cognitive load, nonlinear U-shaped relationships are observed among explainability, cognitive load, and willingness to adopt AI.

Originality/value

We provide design ideas for human-AI team mechanisms in KI-C scenarios, and rationally explain how the U-shaped relationship between AI explainability and cognitive load emerges.

Purpose

The healthcare sector increasingly recognizes how critical sustainable supply chains are to lowering environmental impact, boosting productivity and satisfying public expectations for morally and responsibly provided healthcare. Consequently, the current study aims to thoroughly evaluate the literature on the sustainability of healthcare supply chain management.

Design/methodology/approach

The paper uses a systematic literature review (SLR) technique and bibliometric review to examine the benefactions of different authors, nations and organizations to healthcare sustainability through bibliometric and network analyses.

Findings

The study concludes that the healthcare industry may advance sustainability on all levels by incorporating technology into the fundamentals of sustainability. Patient care is given priority in this proposed approach, which can also help healthcare executives create strategies that support efficient healthcare supply chains.

Research limitations/implications

The research study can serve as a basis for future investigations into additional healthcare management domains, where integrating a sustainable supply chain can yield superior and observable results and bridge deficiencies in management protocols.

Originality/value

Using bibliometric visualization, this study shows the relevance of sustainability in the healthcare supply chain. By identifying its advantages, present-day circumstances, applications and prospective future research fields, the study took up the review and relevance of sustainability in many parts of the healthcare industry.

Purpose

This study aims to analyse Türkiye’s industrial economic complexity index (ECI-IND) for comparison with the ECI-INDs of member countries of the Organization for Economic Co-operation and Development (OECD). It also explores the causal relationship between economic complexity and economic growth in Türkiye.

Design/methodology/approach

Empirical analysis was directed at industrial export baskets consisting of 760 product groups distributed by 130 countries. These data were used to calculate the product complexity index (PCI) and ECI-IND values of these countries. The calculations then served as the basis for examining Türkiye’s economic complexity in comparison with that of OECD countries. Finally, the short- and long-term relationships between the ECI-IND and GDP per capita in Türkiye were investigated using a time series analysis.

Findings

This study’s findings revealed that Türkiye ranked last in terms of economic complexity. The time series analysis showed unidirectional causality between Türkiye’s ECI-IND and its economic growth.

Practical implications

Türkiye should concentrate on ensuring the convergence of its ECI with those of developed countries. Based on the existing literature, it is important for Türkiye to implement policies that (1) increase human capital, (2) expand the share of R&D expenditures out of the GDP and (3) attract foreign direct investments, which advance technology transfer.

Originality/value

This study inquired into the ECI based on industrial products in Türkiye and accordingly provided new data on countries. It also compared Türkiye and OECD nations with respect to this index.

Purpose

Gamification has emerged as a dynamic force in education, with increasing interest in its impact on college students' learning. Most previous research regards gamification as a single element and only focuses on the cognitive level of gamification elements, lacking an overall exploration of the impact mechanism of gamification elements. Against the backdrop of virtual learning communities, we apply the cognition-affection-conation theory to examine the influence of various gamification elements on college students' online learning behaviors, examining both cognitive and affective pathways.

Design/methodology/approach

Data were collected through a predefined questionnaire from 11 Chinese virtual learning communities, with 587 respondents participating in the study. SmartPLS was employed to conduct a Partial Least Squares (PLS) analysis of the research model and test the hypotheses.

Findings

Our findings reveal that immersion and achievement-oriented gamification elements positively impact learning behavior. Conversely, the social gamification element exhibits a negative influence due to social burnout within virtual learning communities. This study pioneers a model to understand the intricate influence mechanisms of gamification elements on college students' online learning behaviors. The model contributes to the enriched exploration and practical application of college students' learning behaviors in virtual learning communities.

Originality/value

Unlike previous studies that often treat gamification as a single element and focus solely on cognitive aspects, this research explores both cognitive and affective pathways using cognition-affection-conation theory. By examining the influence of various gamification elements on college students' online learning behaviors in virtual learning communities, this study provides nuanced insights. In particular, immersion and achievement-oriented gamification elements positively impact learning behavior, while social gamification elements have a negative influence due to social burnout. This comprehensive approach deepens our understanding of how gamification affects students' learning experiences, enriches knowledge, and provides practical insights for educators and instructional designers.