Kybernetes最新文献

Purpose

This research examines the relationship between green innovation and firm performance, focusing on identifying the moderating effects of government subsidies and digital transformation R&D investments. The study aims to provide insights on how firms can leverage green innovation for enhanced performance while addressing potential drawbacks.

Design/methodology/approach

This study adopts a mixed-methods approach, utilizing both analytical models and empirical analyses. It investigates the curvilinear relationship between green innovation and firm performance and explores the moderating roles of government subsidies and digital transformation R&D investments.

Findings

The findings reveal an inverted U-shaped relationship between green innovation and firm performance, indicating that initial investments in green innovation led to performance improvements, but beyond a certain point, the returns diminished. The study also finds that government subsidies and digital transformation R&D investments significantly enhance the positive impact of green innovation up to the optimal threshold and help mitigate negative effects.

Practical implications

The research provides practical guidance for firms on managing their green innovation investments to maximize performance benefits. It also offers insights for policymakers on designing effective subsidies and support mechanisms to promote environmental sustainability and economic growth.

Originality/value

This study contributes to the literature by elucidating the complex relationship between green innovation and firm performance and highlighting the critical roles of government subsidies and digital transformation R&D investments. It offers valuable implications for businesses seeking to balance environmental and economic objectives and policymakers aiming to foster sustainable and profitable practices.

Purpose

Existing research has predominantly concentrated on examining the factors that impact consumer decisions through the lens of potential consumer motivations, neglecting the sentiment mechanisms that propel guest behavioral intentions. This study endeavors to systematically analyze the underlying mechanisms governing how negative reviews exert an influence on potential consumer decisions.

Design/methodology/approach

This paper constructs an “Aspect-based sentiment accumulation” index, a negative or positive affect load, reflecting the degree of consumer sentiment based on affect infusion model and aspect-based sentiment analysis. Initially, it verifies the causal relationship between aspect-based negative load and consumer decisions using ordinary least squares regression. Then, it analyzes the threshold effects of negative affect load on positive affect load and the threshold effects of positive affect load on negative affect load using a panel threshold regression model.

Findings

Aspect-based negative reviews significantly impact consumers’ decisions. Negative affect load and positive affect load exhibit threshold effects on each other, with threshold values varying according to the overall volume of reviews. As the total number of reviews increases, the impact of negative affect load diminishes. The threshold effects for positive affect load showed a predominantly U-shaped course of change. Hosts respond promptly and enthusiastically with detailed, lengthy text, which can aid in mitigating the impact of negative reviews.

Originality/value

The study extends the application of the affect infusion model and enriches the conditions for its theoretical scope. It addresses the research gap by focusing on the threshold effects of negative or positive review sentiment on decision-making in sharing accommodations.

Purpose

A new model for two-sided platforms is presented, incorporating both the original business and an expanded (new) business. Previous studies have neglected the impact of technology R & D on the new business aspect of two-sided platforms. This study addresses this gap by examining the technology R & D effect on the new business while also considering the congestion effect on the original business. It investigates the optimal pricing and user scales for both the original and new businesses. Additionally, the profits of the original business, the new business, and the overall two-sided platform are analyzed.

Design/methodology/approach

Previous studies have overlooked the technology R & D effect on the new business aspect of two-sided platforms. Therefore, this study focuses on examining the technology R & D effect on the new business. Additionally, the congestion effect on the original business is considered. To determine the optimal prices for both sides of the original and new businesses, a game sequence model is introduced.

Findings

The optimal price on the service buyers (defined b side) of new business increases only with regard to technology R & D effect on b side of new business increasing. The optimal price on b side of new business is equal to half of the b-side R & D effect. The optimal profit of original business decreases with regard to the technology R & D effect of new business and cross-market network effect on the services provider (defined s side) between original business and new business increasing, respectively. To gain optimal profit of two-sided platform, the two-sided platform adopts some strategies to improve the congestion.

Originality/value

A new two-sided platform model is stated, in which the technology R & D effect is embraced. The expanded business scenario of two-sided platform is considered, that is, the two-sided platform has one business firstly and a new business is developed or improved of two-sided platform. To solve the prices strategy of original business and new business, a game sequence of the original business and new business is presented.

Purpose

Prioritization of technological skills in China has led to scarce resources for art education. In this study, we tested whether personality traits were associated with creative learning and creative thinking skills, and whether these aspects of creativity were linked with academic achievement. We considered self-efficacy and 21st-century skills as mediating and moderating factors.

Design/methodology/approach

498 art school coaches were recruited from 12 Chinese universities. Coaches reported on their students’ Big Five personality traits, creative thinking skills, creative learning and self-efficacy, 21st-century skills and academic achievement. Data were analyzed with partial least squares structural equation modeling.

Findings

High openness, low conscientiousness, high extraversion and high agreeableness were associated with creative thinking skills, while high openness, low conscientiousness, high agreeableness and low neuroticism were associated with creative learning. Creative thinking and learning skills were both positively associated with academic achievement. Self-efficacy partially mediated the association between creative thinking skills and academic achievement. No moderation effects were identified.

Originality/value

Findings imply that art education would benefit from deeper consideration of individual differences and the promotion of learning environments conducive to creativity.

Purpose

Artificial intelligence (AI) radically transforms organizations, yet ethical AI’s effect on employee innovation remains understudied. Therefore, this study aims to explore whether responsible artificial intelligence (RAI) enhances high-tech employees’ innovative work behavior (IWB) through creative self-efficacy (CSE) and employee mental health and well-being (EMHWB). The study further examines how leaders’ RAI symbolization (LRAIS) moderates RAI’s effect.

Design/methodology/approach

Through structural equation modeling, 441 responses of high-tech firms’ employees from Pakistan were utilized for hypotheses testing via SmartPLS-4.

Findings

The results revealed that second-order RAI enhances employees’ IWB. The effect was supported directly and indirectly through CSE and EMHWB. Findings also showed that LRAIS significantly moderates RAI’s influence on CSE, on the one hand, and EMHWB, on the other.

Practical implications

High-tech firms’ managers can fix AI-outlook issues that impair their employees’ IWB by prioritizing an ethical AI design involving actions like AI control mechanisms, bias checks and algorithmic audits. Similarly, these managers should facilitate RAI discussions and targeted trainings focusing on employees’ cognitive development and well-being. Likewise, RAI embracement programs and evaluations for leadership positions could be incorporated into high-tech firms.

Originality/value

This study advances the mainstream AI literature and addresses a notable gap concerning RAI’s influence on employees’ IWB while grounding in social cognitive theory. Moreover, this study unveils how CSE and EMHWB affect IWB within RAI milieus. Additionally, through signaling theory, it underscores the significance of LRAIS in amplifying the direct association between RAI, CSE, and EMHWB within high-tech firms in emerging markets.

Purpose

Electronic wallets (e-wallet) systems have revolutionized transactional activities, prompting individuals to adopt digital payment methods. This study investigates the determinants of the continuance intention of the e-wallet system Touch 'n Go in Malaysia. We propose a framework integrating the diffusion of innovation theory (DOI) and mental accounting theory, thereby assessing the impacts of product-related factors (convenience, compatibility, perceived risk and perceived compatibility) and the moderating role of personal-related factors [personal innovativeness (PI) and personal anxiety].

Design/methodology/approach

Data were collected involving 381 Malaysian Touch 'n Go users. The partial least squares structural equation modeling (PLS-SEM) was applied as a data analysis technique.

Findings

As demonstrated by the results, convenience serves as a facilitator, while perceived risk acts as an inhibitor, influencing the continuance intention of the application. Compatibility and perceived complexity are found to be insignificant antecedents. However, neither PI nor personal anxiety was found as moderators.

Originality/value

This research brings contributions to the electronic commerce literature by extending the understanding of the predictors and moderators of the continuance intention of Touch 'n Go users in Malaysia. We discuss how these findings implicate the two theories and offer insights for service providers and policymakers to promote the post-adoption intentions of Touch 'n Go.

Purpose

Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

Design/methodology/approach

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

Findings

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

Originality/value

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

Purpose

This study attempts to determine the optimal pricing and warranty strategies for remanufactured products offered by independent remanufacturers (IRs). Specifically, it takes into account price competition and warranty service competition between the original equipment manufacturer (OEM) and IR, ultimately providing recommendations on the selection of warranty service modes for IRs.

Design/methodology/approach

This study considers two warranty modes for IRs: in-housing and outsourcing. Based on game theory, this study identifies the conditions under which the warranty service for remanufactured product is outsourced to retailers in IR-remanufacturing mode. Furthermore, this study investigates how this strategic decision affects closed-loop supply chain (CLSC) operations by comparing the two modes in terms of profit, consumer surplus (CS), quantity and overall social welfare (SW).

Findings

Firstly, the provision strategy for IRs' warranty on remanufactured products depends mainly on the retailer’s warranty cost. If retailers have lower costs for warranties, IR opts to outsource the remanufactured product warranty to the retailer. Second, when retailers offer warranties at a lower cost, IRs prefer outsourcing remanufactured product warranty to retailers. In this way, it will maximize both the remanufacturer’s and retailer’s profits while achieving the optimal total profit for the entire supply chain. However, it’s not beneficial for the OEM. Third, the IR’s preference for warranty service provision strategy is influenced by customers’ acceptance of remanufactured product, customer sensitivity toward remanufactured product warranty and economies of scale in warranty service.

Practical implications

The findings offer operational insights into IR decision-making in selecting warranty service provision strategies for remanufactured products.

Originality/value

This study is among the first to examine warranty provision strategy for IRs in CLSC.

Purpose

The competitiveness of destinations is crucial for tourism. In this context, the study aims to uncover customer satisfaction, experiences, feelings, and thoughts by conducting a comparative analysis of social media comments from various competitive tourism destinations.

Design/methodology/approach

Big data research was conducted to answer the research questions. The data was collected on a social media platform focusing on three destinations in the Mediterranean region. Three methods were employed to analyse the data: sentiment analysis, topic modelling, and named-entity recognition.

Findings

This study addressed traveller satisfaction levels. It identified the topics concerning each destination, examined the emotions expressed by travellers about these topics, explored the potential impact on future behaviour, and investigated the features of the destinations and satisfaction levels about these features. It also identified the prominent food and beverage names in destinations and explored tourists’ preferences regarding these foods and beverages.

Research limitations/implications

The limitations of this study relate to the sample. The data used in this study was solely obtained from a single social media platform and focused on English-only comments. Further research that includes different social media platforms for hotel categories and considers reviews in local languages could capture a broader range of customer opinions and experiences.

Practical implications

Policymakers can gain insight into a destination’s position in the competitive landscape. This study has numerous implications for policymakers in the relevant destinations and managers in the design and implementation of services.

Social implications

The findings of this study can have broader societal implications if considered and implemented by decision-makers and tourism businesses in the context of competitiveness.

Originality/value

The study’s originality lies in integrating multiple disciplines and comparing tourism destinations using big data. This study improves the understanding of competitiveness in three specific Mediterranean destinations. Previous research has focused on different contexts in these Mediterranean destinations. Therefore, the study fills this gap by focusing simultaneously on all three destinations in the context of competitiveness.