Search results

Artificial intelligence (AI) used in service has sparked fundamental changes in how enterprises engage their customers. AI specifically designed for customer service is denoted as service-oriented AI. Through the lens of social information processing theory and the pleasure-arousal-dominance (PAD) emotional state model, this study aims to examine the underlying mechanisms for service-oriented AI anthropomorphism to influence customers' propensity for value co-creation.

Our data were collected from hotel customers who had experienced interactions with service-oriented AI. Through purposive sampling, 350 survey responses were collected. We analyzed the survey data using covariance-based structural equation modeling (CB-SEM).

This study has two key findings. Firstly, customers' propensity for value co-creation is favorably facilitated by the anthropomorphism of service-oriented AI. Secondly, the anthropomorphism of service-oriented AI can strengthen customers' perceptions of cuteness and service capacity, elicit a sense of novelty, and enhance customers' propensity to collaborate with service-oriented AI to create value. These findings address the research gaps by focusing on customer engagement through service-oriented AI and provide a theoretical basis for subsequent practical endeavors in the field.

Integrating the PAD emotional state model with the social information processing theory, this study explores the effects of service-oriented AI's anthropomorphism on customers' propensity for value co-creation.

Neurotechnologies such as brain-computer interfaces (BCIs) are rapidly moving out of laboratories and onto frontline employees' (FLEs) heads. BCIs offer thought-controlled device operation and real-time adjustment of work tasks based on employees’ mental states, balancing the potential for optimal well-being with the risk of exploitative employee treatment. Despite its profound implications, a considerable gap exists in understanding how BCIs affect FLEs. This article’s purpose is to investigate BCIs’ impact on FLEs’ well-being.

This article uses a conceptual approach to synthesize interdisciplinary research from service marketing, neurotechnology and well-being.

This article highlights the expected impact from BCIs on the work environment and conceptualizes what BCIs entail for the service sector and the different BCI types that may be discerned. Second, a conceptual framework is introduced to explicate BCIs’ impact on FLEs’ well-being, identifying two mediating factors (i.e. BCI as a stressor versus BCI as a resource) and three categories of moderating factors that influence this relationship. Third, this article identifies areas for future research on this important topic.

Service firms can benefit from integrating BCIs to enhance efficiency and foster a healthy work environment. This article provides managers with an overview of BCI technology and key implementation considerations.

This article pioneers a systematic examination of BCIs as workplace technology, investigating their influence on FLEs’ well-being.

This study seeks to comprehend if political exposure containing disapproval and different values will affect implicit knowledge sharing (KS) amongst colleagues in the organization. This research examines participants' responses to a colleague's social-media political exposure and their readiness to perform implicit KS to their colleague.

Data collection uses an online questionnaire and a vignette approach. Subsequently, data analysis for 316 finished surveys employs structural equation modelling-partial least squares (SEM-PLS).

The findings show that the perceived-value similarity of political posts of a colleague significantly and indirectly affects workers' readiness to do implicit KS. Besides, likes and trusts also significantly affect workers' readiness to perform implicit KS. While perceived-value similarity strongly shapes likes, likes significantly and positively affect trusts.

Sharing social-media postings associated with political exposure can hinder the implicit KS in organizations and is understudied in the field of knowledge management. Especially, unlike this study which focuses on private companies, previous studies have paid more attention to public enterprises. Besides, this paper's empirical verification is obtained from private organizations in Indonesia, which is also neglected by scholars.

In order to analyze the level of independent controllability and its evolution of high-end equipment manufacturing industry from Jiangsu Province, this article introduces the dual-excitation control line method to construct a comprehensive evaluation model for independent controllability.

Through the collection of information of high-end equipment manufacturing industry's independent and controllable capabilities on different indicators, the three aspects of advancement, autonomy and controllability, an empirical evaluation of 10 enterprises in the high-end equipment cluster in Jiangsu Province was conducted in terms of advancement, autonomy and controllability.

It effectively reveals the area and evolution characteristics of the “reward” and “punishment” of different indicators of each representative enterprise and reflects the development status and different characteristics of each representative enterprise on the three indicators. The research results provide decision-making guidance for enterprises in the management and control of advanced manufacturing systems with independent and controllable capabilities.

Existing research focuses on the evaluation of enterprises' independent controllability only on a single angle or index. This paper maps the dynamic evaluation problem of multiple time-point data to the evaluation problem of single time-point multi-index data and investigates the fluctuation of the performance of the same enterprise under different indexes, so as to comprehensively evaluate the independent controllable level of high-end equipment manufacturing industry and analyze the reasons. Further, this paper first establishes an evaluation index system of independent controllable level of high-end equipment manufacturing industry and quantitatively measures the advanced, independent, controllable and other aspects of typical enterprises in this industry by constructing a double incentive control line evaluation model.