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Chatbots are increasingly used in online retail settings and are becoming a powerful tool for brands to engage customers. However, consumers’ satisfaction with these chatbots is mixed. Thus, this paper aims to investigate how using a social- versus task-oriented anthropomorphic communication style can improve customer satisfaction.

The authors explore the link between the anthropomorphic communication style use and customer perceptions/customer satisfaction in online customer service interactions. Two experiment scenarios were developed to test these links.

Overall, using a social-oriented communication style boosts customer satisfaction. Warmth perception of the chatbot mediates this effect, while chatbot’s anthropomorphised role (servant versus partner) moderates this effect.

This paper enriches the bilateral communication literature by extending the investigation on communication style effects to chatbot service interactions and revealing the psychological process driving the impacts. It also adds to the existing literature on chatbots as a customer service and contributes to the prominent topic examining how consumers react to artificial intelligence that is used to establish and maintain a relationship with them. Additionally, the authors also make contribution to the warmth and competence literature by demonstrating that customers can interpret social cues in chatbot service interactions mainly based on the warmth dimension. Thus, the authors further add to the growing chatbot humanness perception literature and respond to the calls for investigating more anthropomorphic design cues to enhance chatbot humanness. Finally, the authors also provide a way to help reconcile seemingly conflicting prior findings.

The contemporary business environment is characterised by an increasing reliance on artificial intelligence, automation, optimisation, efficient communication and data-driven decision making. Based on the limited academic literature that examines the managerial perspective on enterprise chatbots, the paper aims to explore organisational needs and expectations for enterprise chatbots from a managerial perspective, assesses the relationship between managerial knowledge and managerial opinion regarding enterprise chatbots, and delivers a framework for integrating chatbots into the digital workforce.

The paper presents a quantitative design. An online, self-administered survey yielded 111 valid responses from managers in service and manufacturing organisations based on convenience and snowball sampling strategies. Given the nature of the data and the research questions, the research was conducted using principal component analysis, parallel analysis, correlation, internal consistency and difference in means tests.

This research explores the managerial perspective on enterprise chatbots from multiple perspectives (i.e., adoption, suitability, development requirements, benefits, barriers, performance and implications), presents a heat map of the average level of chatbot need across industries and business units, highlights the urgent need for education and training initiatives targeted at decision makers, and provides a strategic framework for successful chatbot implementation.

This study equips managers and practitioners dealing with enterprise chatbots with knowledge to effectively leverage the expected benefits of investing in this technology for their organisations. It offers direction for developers in designing chatbots that align with organisational expectations, capabilities and skills.

Insights for managers, researchers and chatbot developers are provided. The work complements the few academic studies that examine enterprise chatbots from a managerial perspective and enriches related commercial studies with more rigourous statistical analysis. The paper contributes to the ongoing discourse on decision-making in the context of technology development, integration and education.

This paper aims to addresses an important gap in anthropomorphism research by examining the individual-level factors that correlate with anthropomorphic tendency.

The extant psychology, marketing and consumer psychology literature is reviewed, and eight hypotheses devised. Data from 509 online survey respondents are analysed to identify individual characteristics associated with anthropomorphic tendency.

The results reveal that anthropomorphic tendency varies by individual and is significantly related to personality, age, relationship status, personal connection to animals and experiential thinking.

This paper extends on recent research into the individual nature of anthropomorphic tendency, once thought to be a universal trait. Given that this paper is the first of its kind, testing of further traits is merited. It is suggested that future research further examine personality, as well as other elements of individual difference, and test the role of anthropomorphic tendency in the development of processing abilities with age.

Findings show that anthropomorphic tendency may prove to be a key variable in the segmentation of markets and the design of marketing communications, and that younger, single, more creative, conscientious consumers are an appropriate target for anthropomorphic messages. The importance of personal connection to animals, as well as experiential thinking, is also highlighted.

Given the importance of anthropomorphic tendency for the processing of messages involving non-human endorsers, as well as the formation of relevant attitudes and behaviours, this paper fulfils an identified need to further understand the characteristics of those high on this tendency.

This study presents one of the earliest empirical investigations on how brand chatbots' anthropomorphic design and social presence communication strategies may improve consumer evaluation outcomes via the mediators of parasocial interaction and perceived dialogue.

This study employs a 2 (high vs. low social presence communication) by 2 (anthropomorphic vs. non-anthropomorphic bot profile) between-subject experimental design to evaluate how chatbots' high social presence communication and anthropomorphic profile design may enhance perceptions of parasocial interactions and dialogue with the chatbot, which in turn drive user engagement, interaction satisfaction and attitude toward the represented brand.

The influences of chatbots' high social presence communication on consumer engagement outcomes are mediated by perceived parasocial interaction and dialogue. Additionally, chatbots' anthropomorphic profile design can boost the positive effects of social presence communication via the psychological mediators.

This study advances the interactive marketing literature by focusing on an emerging interactive technology, chatbots. Additionally, distinct from prior chatbot studies that focused on the utilitarian use of chatbots for online customer support, this study not only examines which factors of chatbot communication and profile design may drive chatbot effectiveness but also examines the mechanism underlying the messaging and design effects on consumer engagement. The findings highlight the mediating role of interpersonal factors of parasocial interaction and perceived dialogue.

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

As the social media platform becomes an ever more important communication channel between company and customer, companies are learning how they can best utilize social media to better communicate their brands with customers. The purpose of this paper is to explore the communication tactics adopted by the enterprise microblogs using a communication framework. Further, the authors hope to find out how these communication tactics influence customer brand experience (BE) and subsequently brand loyalty.

First, to identify the communication tactics used by enterprise microblogs, the authors recruited six active microblog users and listed all possible characteristics of enterprise microblogs that could increase customers’ fondness for the brand. Second, based on the listed 19 characteristics and existing theories, the authors pre-classified and conceptualized the content and style tactics categories. The authors also followed a sorting procedure to verify our classification. Finally, based on the sorted characteristics and previous research, the authors designed a questionnaire and 459 sets of valid data were collected from enterprise microblog users.

The communication tactics are classified into two dimensions, namely content tactics and style tactics. The content tactics include content diversity, content accuracy and content timeliness, and the style tactics include impression enhancement style and interactivity enhancement style. The results reveal that the communication content and style tactics significantly enhance overall customer BE and further brand loyalty. The study results also show that style tactics exert more influence on BE than content tactics.

This paper highlights the company’s important role in company-customer communication on social media, and categorizes the effective communication tactics used by the enterprise microblog within a communication framework. Companies could build brand loyalty by enhancing users’ BE using effective communication. The communication perspective and measures of the communication tactics in this study provide an ideal background for future research on IT-based company-customer interaction.

Enterprises often use anthropomorphic images to display products. In this study, by discussing the differences of the anthropomorphic images of juxtaposition and fusion, the authors can distinguish the boundary conditions of the influence of different visual object structures on consumers' attention.

Based on schema theory and information processing theory and using eye movement methods, this study analyzed the attractiveness of anthropomorphic images to consumers under different congruence levels through experiments of 2 (congruence: high and low) *2(visual object structure: juxtaposition and fusion)*2(self-construct: interdependent and independent). This study discusses the difference in the attractiveness of interdependent and independent consumers in the context of high congruence, juxtaposition and fusion of two visual object structures.

The results show that compared with the low congruence anthropomorphic image, the high congruence anthropomorphic image can attract more attention of consumers. In the case of low compatibility of anthropomorphic images, the juxtaposition structure of anthropomorphic images is more attractive to consumers than the fusion structure. In the case of high compatibility of anthropomorphic images, for independent self-consumers, the attraction of fusion structure image is higher than the juxtaposition image, and for interdependent self-consumers, the attraction of juxtaposition image is higher than the fusion image.

The conclusion enriches the anthropomorphic marketing theory. It reveals different degrees of attention paid to anthropomorphic image by consumers of different types of self-construct. Eye movement methods provide a new perspective for the study of anthropomorphic marketing and provide a reference for enterprises to publicize products or services through anthropomorphic image.

Customer service conversations are becoming increasingly digital and automated, leaving service encounters impersonal. The purpose of this paper is to identify how customer service agents and conversational artificial intelligence (AI) applications can provide a personal touch and improve the customer experience in customer service. The authors offer a conceptual framework delineating how text-based customer service communication should be designed to increase relational personalization.

This paper presents a systematic literature review on conversation styles of conversational AI and integrates the extant research to inform the development of the proposed conceptual framework. Using social information processing theory as a theoretical lens, the authors extend the concept of relational personalization for text-based customer service communication.

The conceptual framework identifies conversation styles, whose degree of expression needs to be personalized to provide a personal touch and improve the customer experience in service. The personalization of these conversation styles depends on available psychological and individual customer knowledge, contextual factors such as the interaction and service type, as well as the freedom of communication the conversational AI or customer service agent has.

The article is the first to conduct a systematic literature review on conversation styles of conversational AI in customer service and to conceptualize critical elements of text-based customer service communication required to provide a personal touch with conversational AI. Furthermore, the authors provide managerial implications to advance customer service conversations with three types of conversational AI applications used in collaboration with customer service agents, namely conversational analytics, conversational coaching and chatbots.

This paper aims to introduce the human arm movement primitive (HAMP) to express and plan the motions of anthropomorphic arms. The task planning method is established for the minimum task cost and a novel human-like motion planning method based on the HAMPs is proposed to help humans better understand and plan the motions of anthropomorphic arms.

The HAMPs are extracted based on the structure and motion expression of the human arm. A method to slice the complex tasks into simple subtasks and sort subtasks is proposed. Then, a novel human-like motion planning method is built through the selection, sequencing and quantification of HAMPs. Finally, the HAMPs are mapped to the traditional joint angles of a robot by an analytical inverse kinematics method to control the anthropomorphic arms.

For the exploration of the motion laws of the human arm, the human arm motion capture experiments on 12 subjects are performed. The results show that the motion laws of human arm are reflected in the selection, sequencing and quantification of HAMPs. These motion laws can facilitate the human-like motion planning of anthropomorphic arms.

This study presents the HAMPs and a method for selecting, sequencing and quantifying them in human-like style, which leads to a new motion planning method for the anthropomorphic arms. A similar methodology is suitable for robots with anthropomorphic arms such as service robots, upper extremity exoskeleton robots and humanoid robots.

Driven by artificial intelligence technology, chatbots have begun to play an important customer service role in the online retail environment. This study aims to explore how conversational styles improve the interaction experience between consumers and chatbots in different social crowding environments, and the moderating role of product categories is considered.

Three studies are conducted to understand the influences of conversational styles, social crowding and product categories on consumer acceptance, assessed using situational experiments and questions.

In a low social crowding environment, consumers prefer chatbots with a social-oriented (vs. task-oriented) conversational style, while in a high social crowding environment, consumers prefer a task-oriented (vs. social-oriented) conversational style, and warmth and competence mediate these effects. The moderating effect of product categories is supported.

This study expands the application of the stereotype content model to improve the interaction experience level between consumers and chatbots in online retail. The findings can provide managerial suggestions for retailers to select a chatbot's conversational style and promote a more continuous interaction between consumers and chatbots.