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The study aims to identify the practical borders of AI legal personality and accountability in human-centric services.

Using a framework tailored for AI studies, this research analyses structured interview data collected from auditors based in Poland.

The study identified new constructs to complement the taxonomy of arguments for AI legal personality: cognitive strain, consciousness, cyborg paradox, reasoning replicability, relativism, AI misuse, excessive human effort and substitution.

The insights presented herein are primarily derived from the perspectives of Polish auditors. There is a need for further exploration into the viewpoints of other key stakeholders, such as lawyers, judges and policymakers, across various global contexts.

The findings of this study hold significant potential to guide the formulation of regulatory frameworks tailored to AI applications in human-centric services. The proposed sui generis AI personality institution offers a dynamic and adaptable alternative to conventional legal personality models.

The outcomes of this research contribute to the ongoing public discourse on AI’s societal impact. It encourages a balanced assessment of the potential advantages and challenges associated with granting legal personality to AI systems.

This paper advocates for establishing a sui generis AI personality institution alongside a joint accountability model. This dual framework addresses the current uncertainties surrounding human, general AI and super AI characteristics and facilitates the joint accountability of responsible AI entities and their ultimate beneficiaries.

Based on organizational learning theory, this study aims to investigate the performance consequences and potential contextual factors of outward foreign direct investment (OFDI) persistence.

A regression analysis was conducted on a sample of 19,950 OFDI events of 1,425 A-share listed Chinese enterprises from 2008 to 2022. The estimator used was ordinary least squares with residual analysis, which allowed us to obtain robust and reliable results.

The results indicated that persistence in both greenfield investments and cross-border M&As had a significant and positive impact on firm performance, and such relationship was positively moderated by organizational absorptive capacity.

This study only tested the economic performance of OFDI persistence rather than innovation and social performance. Exploring the effects of OFDI persistence on other aspects may also add new insights to the persistence literature. Besides absorptive capacity, it might be useful to conduct a more comprehensive consideration of moderators in the future.

This paper contributes to the research on the temporal dimension of internationalization by introducing the concept of OFDI persistence. Additionally, we used the OFDI spell to capture the notion of OFDI persistence, which is an endeavor to overcome the shortcomings of the traditional indicator. Finally, this paper also contributes to the organizational learning perspective by applying it to analyze persistent OFDI operations.

The research applied service-dominant logic of marketing theory, a customer-centered and relational that principally grounded in service relationships and actor networks. In actor networks, salespeople provide their skills and knowledge, such as expertise, service quality, ethics and shared value to cocreate value for buyers. Therefore, this study explores the attributes of salespeople that influence the quality of the relationship (trust and satisfaction) and, as a result, loyalty in the context of the business-to-business (B2B) relationship in the Taiwan market.

A causal relationship and survey research design are applied. The study collected 266 valid responses from B2B account managers representing various companies and industries. Structural equation modeling (SEM) was applied to test the hypotheses.

The results showed that salespeople’s expertise demonstrated the most significant influence on both trust and satisfaction, followed by ethics, service quality and share value, in a descending order of impact. Consequently, trust and satisfaction had a significant impact on customer loyalty.

The four attributes of salespeople play a pivotal role in establishing lasting relationships and maximizing the customer lifetime value. To achieve long-term success in customer interactions and relationships, a well-rounded salesperson should diligently strive to excel in all these attributes.

The novelty and contribution of this study are twofold. First, investigating the quality of the relationship in the context of Taiwanese manufacturers in a B2B setting is still rare, and this is the study first to explore the Taiwanese B2B relationship with its global customers. As Taiwanese manufacturers play a pivotal role in the global supply chain, the research findings have symbolic meaning and practical implications for global business partners. Second, drawing from service-dominant logic theory, this research takes an integrative view by examining the attributes (expertise, service quality, shared value and ethics) that influence and establish a quality trusting relationship and consumer loyalty in the B2B context.

Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.

Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.

Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.

In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.

This paper aims to investigate the impact of China’s Green Credit Guidelines (GCG) policy on the environmental, social and governance (ESG) scores of restricted enterprises and examine firm’s speculative behavior in response to the policy.

This paper views the GCG policy proposed in 2012 as a quasinatural experiment and uses difference-in-differences (DID) model to evaluate its influence on the ESG scores of Chinese nonfinancial A-share listed enterprises from 2007 to 2019. Robustness tests include the propensity score matching (PSM)–DID method and permutation tests.

The GCG policy significantly increases the ESG scores of restricted enterprises, particularly enhancing environmental (E) performance. However, it only improves the social (S) and governance (G) performance of firms heavily reliant on bank credit, indicating speculative behavior by enterprises. Increased Government attention, a higher proportion of female executives and more developed local green finance reduce speculative behavior, while executives with financial backgrounds promote it.

Governments should mandate standardized ESG reporting and monitor restricted enterprises, banks should monitor speculative behavior and firms should integrate ESG into their long-term strategies to support sustainable development.

The results provide evidence of the effectiveness of implementing the GCG policy in China and offer guidance for better promoting green credit policy in developing countries, contributing to the transition toward a more sustainable future.

To the best of the authors’ knowledge, this paper is the first to explore if the GCG policy’s asymmetric effects on ESG components are due to enterprise speculative behavior and examines the factors influencing this behavior, providing insights for regulators to better implement the GCG policy to promote sustainable development.

Coordinating low-carbonization and digitalization is a practical implementation pathway to achieve high-quality economic development. Regions are under great emission reduction pressure to achieve low-carbon development. However, why and how regional emission reduction pressure influences enterprise digital transformation is lacking in the literature. This study empirically tests the impact of emission reduction pressure on enterprise digital transformation and its mechanism.

This article takes the data of non-financial listed companies from 2011 to 2020 as a sample. The digital transformation index is measured by entropy value method. The bidirectional fixed effect model was used to test the hypothesis.

The research results show that emission reduction pressure forces enterprise digital transformation. The mechanism lies in that emission reduction pressure improves digital transformation by promoting enterprise innovation, and digital economy moderates the nexus between emission reduction pressure and digital transformation. Furthermore, the effect of emission reduction pressure on digital transformation is more significant for non-state-owned, mature and high-tech enterprises.

This paper discusses the mediating role of enterprise innovation between carbon emission reduction pressure and enterprise digital transformation, as well as the moderating role of digital economy. The research expands the body of knowledge about dual carbon targets, digitization and technological innovation. The author’s findings help update the impact of regional digital economy development on enterprise digital transformation. It also provides theoretical guidance for the realization of digital transformation by enterprise innovation.

This study investigates two internationalization strategies, foreign direct investment (FDI) expansion and export expansion, and their effects on the innovation performance of Chinese multinational enterprises (MNEs). Additionally, it explores the moderating roles of both formal and informal political connections in the relationship between these internationalization strategies and innovation performance.

The hypotheses were tested using the Poisson panel model and data on 2,106 observations from 645 Chinese-listed firms between 2010 and 2017.

FDI expansion significantly enhances the innovation performance of Chinese MNEs compared to export expansion. Moreover, formal and informal political connections are found to have distinct moderating effects: formal political connections amplify the positive effect of FDI expansion on firm innovation, whereas informal political connections tend to weaken it.

This study contributes to the discourse on innovation and political connections, especially in the context of EMNEs. It enriches the theoretical understanding of internationalization strategies and innovation performance in EMEs, contrasting with the technology-utilization motives observed in MNEs from developed economies.

Studies have explored the determinants of customer advocacy because of customer advocacy's vital role in improving the efficiency and effectiveness of marketing. The current research complements the existing literature in the hospitality field by examining the association between restaurant innovativeness and customer advocacy while also investigating the mediating roles of self-image congruity and customer engagement.

The statistical software AMOS version 25 and bootstrapping were employed to test the hypotheses. Purposive sampling was employed for participant recruitment, and a self-administered questionnaire was used to collect data. Data were collected from Taiwanese customers who had dined at selected restaurants.

The results from 385 restaurant customers reported that self-image congruity had an indirect impact on customer advocacy through customer engagement. Customer advocacy was influenced by restaurant innovativeness through the mediation of customer engagement. The influence of restaurant innovativeness on customer advocacy was positively and sequentially mediated by self-image congruity and customer engagement.

Restaurant innovativeness is linked to customer advocacy through self-image congruity and customer engagement. Thus, restaurant managers should implement strategies focusing on innovativeness to improve self-image congruity and engagement among customers.

The current research may be the first to provide a research model that explores restaurant innovativeness, self-image congruity, customer engagement and customer advocacy in the hospitality context. This study also has practical implications for enhancing customer advocacy.

The purpose of this review is to provide a conceptual framework of consumer engagement behavior in the value co-creation process of healthcare services, and further understand the current knowledge maps and advances.

Specifically, the scoping review methodology is used to synthesize the extant findings. The authors first develop the inclusion/exclusion criteria to evaluate the source material for the review; then, the authors further conduct the literature refinement to select the final data sample. As such, the authors extract and analyze the information derived from these articles.

The authors found most related studies focus on exploring patients' engagement behavior in the value co-creation process, especially those with chronic disease; the findings also reveal that consumers are most likely to engage in the value co-creation process of healthcare services by seeking or sharing health information; also, consumers engagement behavior is mainly driven by individual, interactive, and technological factors; moreover, consumer engagement in the value co-creation of healthcare services are more likely to achieve positive health and behavioral outcomes.

The role of consumers has gradually shifted from that of passive recipients to that of active participants in the healthcare value co-creation process. Consumer engagement behavior is the key premise for the realization of healthcare value co-creation, and it has received increasing attention both academically and practically. By unearthing the conceptual framework of consumer engagement behavior in the value co-creation process of healthcare services, this study provides a systematic understanding and serves as a useful resource for future research and practice.

Co-creation of services (CCOS) is a collaborative strategy that emphasises customer involvement and their expertise to increase the value of the service experience. In the service ecosystem, artificial intelligence (AI) plays a key role in value co-creation. Therefore, this study is undertaken to empirically uncover how AI can empower CCOS.

The source data were collected from 305 service provider respondents and quantitative methodology was applied for data analysis.

New service development augmented with AI provides tangible value to service providers while also providing intangible value to supportive customers. With AI, service providers adapt to new innovations and enrich additional information, which eventually outperforms human-created services.

AI adoption for CCOS empowerment in service businesses brings “service-market fit”, which represents the significant benefits wherein customers contribute to creativity, intuition, and contextual awareness of services, and AI contributes to large-scale service-related analysis by handling volumes of data, service personalisation, and more time to focus on challenging problems of the market.

This study presents theoretical concepts on AI-empowered CCOS, AI technological innovativeness, customer participation in human-AI interaction, AI-powered customer expertise, and perceived benefits in CCOS, and subsequently discusses the CCOS empowerment framework. Then, it proposes a novel conceptual model based on the theoretical concepts and empirically measures and validates the intention to adopt AI for CCOS empowerment. Overall, the study contributes to novel insight on empowering service co-creation with AI.