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Various consumer-facing artificial intelligence (AI) applications are used to interact with consumers at all purchase stages, and related research has sharply increased. This study aims to synthesize the literature related to consumer–AI interaction using the customer journey framework, identify the factors affecting AI's effectiveness in interactive marketing and offer an agenda for future research.

This study undertakes a framework-based systematic review of 239 articles on AI in marketing from the consumer perspective published in peer-reviewed journals from 2007 to 2021.

This review identifies the roles of AI touch points and factors affecting the acceptance and effectiveness of consumer–AI interaction in each stage of the customer journey.

This study is the first to review the existing literature using a customer journey framework to identify the factors that influence customer interactions with AI touch points at each purchase stage and pave the way for future research.

Online retail platform corporate sustainable development (ORPCSD) has garnered significant interest and appeal among consumers. However, no scale has been developed to measure consumer perceptions of ORPCSD. Therefore, this study aimed to delineate the conceptual framework and dimensions underlying these perceptions and construct a reliable and valid measurement tool.

This study employed established qualitative and quantitative methods in two studies. In the first study, the dimensions and measurement items of consumer perceptions of ORPCSD were proposed using the grounded method. In the second study, the measurement scale was refined and validated using exploratory factor analysis, confirmatory factor analysis, and nomological validity examination.

The results indicated that consumer perception of ORPCSD consisted of three dimensions: economic, social, and environmental sustainability. The measurement scale for these dimensions comprised 25 items, demonstrating excellent psychometric properties.

This study contributes original insights by enhancing the current understanding of consumer perceptions of ORPCSD. Additionally, it provides researchers and managers with psychometric metrics to gauge these perceptions and offers actionable strategies for sustainable marketing initiatives.

This paper studies the relationships among consumers’ perceptions of brand personality, consumers’ brand attitudes and brand-owned social media content marketing (SMCM). The moderating effect of the brand content relevancy was also assessed.

A conceptual model was established and examined using two experiments with a total of 363 participants. Hierarchical regression analysis and an analysis of variance were performed to test seven research hypotheses.

Results show that the three forms of brand-owned SMCM, namely: conversation, storytelling and customer interaction and participation, are positively correlated with consumers’ brand personality perceptions and brand attitudes. Also, consumers’ perceptions of brand personality can partially mediate the relationship between brand-owned content marketing and consumers’ brand attitudes. Furthermore, the brand content relevancy does not show a moderating effect on the relationship between content marketing and consumers’ brand personality perceptions or brand attitudes.

First, a framework was established to delineate those paths by which owned social media content marketing (OSMCM) influences consumers’ attitudes towards a brand. Second, the study demonstrates the importance of conversation as a powerful method of OSMCM. Third, with respect to content in marketing strategies, firms do not need to confine themselves to a narrow scope of content or information that is closely related to the brands alone.

In order to effectively promote the deep integration of artificial intelligence and the real economy and empower real enterprises to improve quality and efficiency, this study regards the CEO as a high-end innovation resource and aims to empirically test the impact of scholar-type CEOs on the industrial artificial intelligence (AI) transformation of manufacturing enterprises.

Grounded on the upper echelons theory, this paper preliminarily selects A-share manufacturing listed companies in Shanghai Stock Exchange and Shenzhen Stock Exchange that are affiliated to enterprise groups from 2014 to 2020 as samples. Furthermore, the Logit regression is conducted to analyze the influence of scholar-type CEOs about industrial AI transformation.

The results show that scholar-type CEO plays a significant role in promoting industrial AI transformation. The parent-subsidiary corporations executives' ties positively moderates the impact of scholar-type CEOs on industrial AI transformation. Further, internal control quality plays a partial mediating role between scholar-type CEOs and industrial AI transformation. Compared with private enterprises, scholar-type CEOs play a stronger role in promoting industrial AI transformation of state-owned enterprises.

First, this paper expands the research related to the influencing factors of industrial AI transformation based on upper echelons theory and clarifies the influencing mechanism of scholar-type CEOs affecting industrial AI transformation from the perspective of executives' behavior. Second, this study further enriches the research framework on the economic consequences of scholar-type CEOs and provides a useful supplement to the research literature in the field of upper echelons theory. Third, this paper is not limited to a single enterprise but involves the management practice of resource allocation within the enterprise groups, further clarifies the internal logic of the decision-making of industrial AI transformation of listed companies within the framework of enterprise groups, providing theoretical reference for the scientific design of the governance mechanism of parent-subsidiary companies.

The purpose of this study is to provide insights and guidance for practitioners in terms of ensuring rigorous ethical and moral conduct in artificial intelligence (AI) hiring and implementation.

The research employed two experimental designs and one pilot study to investigate the ethical and moral implications of different levels of AI implementation in the hospitality industry, the intersection of self-congruency and ethical considerations when AI replaces human service providers and the impact of psychological distance associated with AI on individuals' ethical and moral considerations. These research methods included surveys and experimental manipulations to gather and analyze relevant data.

Findings provide valuable insights into the ethical and moral dimensions of AI implementation, the influence of self-congruency on ethical considerations and the role of psychological distance in individuals’ ethical evaluations. They contribute to the development of guidelines and practices for the responsible and ethical implementation of AI in various industries, including the hospitality sector.

The study highlights the importance of exercising rigorous ethical-moral AI hiring and implementation practices to ensure AI principles and enforcement operations in the restaurant industry. It provides practitioners with useful insights into how AI-robotization can improve ethical and moral standards.

The study contributes to the literature by providing insights into the ethical and moral implications of AI service robots in the hospitality industry. Additionally, the study explores the relationship between psychological distance and acceptance of AI-intervened service, which has not been extensively studied in the literature.