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This study aims to investigate how chatbots’ warmth and competence affect customer behavioural expectation (i.e. purchase, recommendation) through perceived humanness and perceived persuasiveness. Moreover, prior knowledge of chatbot is considered the boundary condition of the effects of chatbots’ warmth and competence.

A lab-in-field experiment with 213 participants and a scenario-based experiment of 186 participants were used to test the model using partial least squares structural equation modelling via SmartPLS 4.

Chatbot warmth positively affects customer behavioural expectation through perceived humanness while chatbot competence positively affects customer behavioural expectation through perceived persuasiveness. Prior knowledge of chatbot positively moderates the effect of chatbot warmth on perceived humanness.

This study provides nuanced insights into the effects of chatbots’ warmth and competence on customer behavioural expectation. Future studies could extend the model by exploring additional boundary conditions of the effects of chatbots’ warmth and competence in different generations.

This study offers insightful suggestions for marketing managers on how to impress and convert online customers through designing verbal scripts in customer−chatbot conversations that encourage the customers to anthropomorphise the chatbots.

This study probes into the effects of chatbots’ warmth and competence on customer behavioural expectation by proposing and examining a novel research model that incorporates perceived humanness and perceived persuasiveness as the explanatory mechanisms and prior knowledge of chatbot as the boundary condition.

Though originality is a requirement for copyright protection, the term is not defined, leaving room for differing interpretations. Over the years, there has been a shift in the yardstick for determining originality. The lack of definition gives room for ambiguity and creates hurdle for protection. The difficulty in assessment of originality is more felt in certain forms of work like music, which has its own theories and limitations. Absence of determining tests creates uncertainty for the authors to draw the line between inspiration and infringement. This paper aims to define originality as applicable to each subject matter.

The methodology used is a qualitative analytical approach and draws from theories and relevant case laws.

The requirement of “originality” as laid down in the Copyright Act has to be defined with precision. The requirement of originality for different categories of subject matter encompassed within copyright law will differ and so the term should be redefined with respect to each subject matter.

This paper is an original work and canvasses for a definition of the term originality in the Copyright Act with reference to the various subject matter entitled to protection.

South Africa’s wool industry plays an important role in the agricultural sector. The wool industry provides a valuable source of income for farmers who practice sustainable farming practices. However, wool farmers face numerous challenges, such as wool contamination, dirty wool and producing good-quality wool. Good-quality wool is determined by fibre diameter, clean yield, vegetable matter and staple length. This study aims to address these challenges.

A multiple regression analysis of price (R/kg) of White wool and Merino wool was applied to four variables fibre diameter: vegetable matter, clean yield and staple length. The analysis was based on the data for the 2009–2019 data from Cape Wools auctions.

Fibre diameter, clean yield and staple length, with exception of vegetable matter, made a statistically significant contribution to the determination of wool price after all other independent variables were controlled for (p < 0.05). A one-unit (micron) increase in fibre diameter resulted in a 0.404-unit decrease in wool price (R/kg). A one-unit (mm) increase in staple length resulted in a 0.022-unit increase in wool price (R/kg). There was no statistically significant association between vegetable matter and wool price. A one-unit increase in clean yield was associated with a 0.111-unit increase in wool price (R/kg).

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

Since wool fleeces consist of the largest portion of wool shorn from sheep, it is important for wool farmers to focus on wool with low fibre diameter, high clean yield percentage, low percentage of vegetable matter content and good length of the wool.

In a developing country such as South Africa, this study is important for the following reason. It is understanding the wool characteristics that have the most significance influence on the determination of wool price for Merino wool and White wool might effectively help the wool farmers to adapt their production systems to improve the wool characteristics that determine wool price.

This study identified a need for a study to be conducted on all wool classes.

While prior research has examined customer acceptance of humanized chatbots, the mechanisms through which they influence customer value creation remain unclear. This study aims to investigate the emerging concept of Perceived Humanization (PH), examining how hedonic motivation, social influence and anthropomorphism influence value creation through the serial mediation of PH and trust. The moderating roles of rapport and social presence are also explored.

Based on data from an online survey involving 257 respondents, this study employs Partial Least Squares Structural Equation Modeling utilizing SmartPLS3 software.

Hedonic motivation leads to value creation via two routes: PH and affective trust; and PH and cognitive trust. Social influence and anthropomorphism also positively impact value creation through similar pathways. Rapport moderates the impact of social influence on PH, while social presence moderates the relationship between PH and both affective and cognitive trust. A cross-cultural analysis of China, India and New Zealand highlights varying cultural dimensions influencing PH and its effects on value creation.

For practitioners in the tourism industry, the findings highlight the strategic importance of enhancing PH in chatbot interactions. By understanding and optimizing these elements, businesses can significantly improve their customer value-creation process.

This study contributes to the service marketing literature by generating a comprehensive framework for the comprehension and application of PH. Its cross-cultural perspective provides rich insights, offering valuable information for service marketers aiming to thrive in the dynamic and competitive tourism industry.

This study is designed to investigate a critical association between social media addiction and employee sleep while considering its implications for employee well-being and performance in the hospitality industry.

Based on adapted measures for the study variables, an electronic questionnaire was designed and used for the survey administered in the chain-restaurants of Pakistan. Through a non-probability convenient sampling survey, a total of 347 usable responses were obtained and analyzed for testing the hypothesized research model.

Results reveal negative associations between social media addiction, sleep quality, employee performance and well-being. The results have further shown sleep quality as an underlying mediating reason that explains the associations between social media addiction, employee performance and well-being.

The study addresses a gap in the literature by examining rarely explored factors such as social media addiction and sleep quality at the same time investigating its impact on performance and well-being of service employees. Significant implications for scholars and practitioners of the hospitality industry have been discussed while highlighting limitations and directions for future research.

Along with the development of the robotics industry, service robots have been gradually used in the hospitality industry. Nevertheless, service robot categorization and the fulfillment of the cognitive and emotional needs of consumers by hotel service robots have yet to be fully explored. Hence, the purpose of this study are to categorize hotel service robots, to explore consumers’ robot hotel experience, to identify the consumers’ preference of hotel service robot in general, to reveal consumers’ preference for hotel service robots based on their fulfillment of emotional needs and to examine the completion of cognitive–analytical and emotional–social tasks.

Through in-depth interviews with technology managers and questionnaire survey among consumers who have and have not had robot hotel stay experience to achieve the aforementioned research objectives.

Findings of in-depth interviews show that service robots can be categorized as check-in/out robots, artificial intelligence (AI) robots and service delivery robots. Results of questionnaire survey indicate that consumers prefer non-humanoid robots (n = 213, p = 47.87%) among check-in/out robots, the Xiaodu Smart Display (n = 163, p = 36. 63%) among the AI robots and the machine-shaped robot porter (I) (n = 178, p = 40.00%) among the service delivery robots.

This study provides implications, such as the adoption of robot-shaped AI with a screen display, to hotel managers to meet the needs of consumers regarding the completion of cognitive–analytical and emotional–social tasks of robots.

This study extends uncanny valley theory by identifying preference for the shape and functions of different categories of service robots and contributes to the limited literature on hotel robots.

This study explores features that impact consumers' purchase intention through artificial intelligence (AI), because it is believed that through artificial intelligence, consumers' intention to purchase grows significantly, especially in the retail sector, whereby retailers provide lucrative offers to motivate consumers. The study develops a theoretical framework based on media-richness theory to investigate the role of perceived anthropomorphism toward an intention to purchase products using AI.

The study is based on cross-sectional data through an online survey. The data have been analyzed using PLS-SEM and SPSS PROCESS macro.

The results show that consumers tend to demand anthropomorphized products to gain a better shopping experience and, therefore, demand features that attract and motivate them to purchase through artificial intelligence via mediating variables, such as perceived animacy and perceived intelligence. Moreover, trust in artificial intelligence moderates the relationship between perceived anthropomorphism and perceived animacy.

The study investigates and concludes with managerial and academic insights into consumer purchase intention through artificial intelligence in the retail and marketing sector.

With the increasing use of robots in service scenarios in hospitality industries, service failure frequently occurs during the service process, and consumers may react differently toward humanoid vs. nonhumanoid robots due to different performance expectancies. This study focuses on consumers' reactions to service failures by humanoid vs. nonhumanoid robots and the different impacts on brand forgiveness and revisit intentions through performance expectancy for different genders.

The study used a sample of 280 participants to test the moderated chain mediation model. The participants were instructed to report their performance expectancies for humanoid/nonhumanoid robots and imagine a hotel check-in scenario in which a service failure occurs. Brand forgiveness, brand revisit intention and other demographic information were assessed.

The results show that consumers have higher performance expectancy for nonhumanoid robots. This performance expectancy generates brand forgiveness and revisit intentions for male consumers but does not affect female consumers' forgiveness and revisit behaviors.

This study contributes to the literature by taking a long-term perspective to investigate the outcomes after service failure, providing evidence for pending questions in previous studies and enriching studies of gender differences. Additionally, this study provides practical implications to consider the use of anthropomorphism in robots, advocate for functional confidence in robots and target consumers across genders.

This study explores how customers' individual characteristics and perceptions affect acceptance of service robots as a hotel workforce. The Interactive Technology Acceptance Model (iTAM) has inspired us to investigate effects of customers' technological self-efficacy, perceived interactivity, sense of utility, and enjoyment-level of acceptance related to hotel-service robots as staff.

Data were collected from 224 customers via an online questionnaire conducted in the period April–June 2022 by convenience sampling, and then analyzed by using partial least squares – structural equation modeling (PLS-SEM).

The findings show that customers' technological self-efficacy and perceived interactivity with service robots enhances perceived usefulness and perceived enjoyment, serving as functional and emotional value components of service robots. They also demonstrate that robot's interactivity outweighs other robot's value components, such as perceived usefulness and perceived enjoyment for acceptance of service robots as employees in hotels.

While empirically validating the iTAM, this study emphasizes service robot interactivity as the most important aspect for customers' acceptance, and it adds a new perspective regarding the underexplored role of the customer-robot interface. Combining specific dimensions from different technology acceptance models (functional/socio-emotional/relational; utilitarian/hedonic) the study contributes to the service robot literature currently missing a more holistic understanding of consumers' experience and adoption drivers, and it provides managerial guidance on how to successfully implement service robots in hotel environments.

Explore how the degree of humanization affects user misconduct, and provide effective misconduct prevention measures for the wide application of artificial intelligence in the future.

Based on the “Uncanny Valley theory”, three experiments were conducted to explore the relationship between the degree of humanization of service machines and user misbehavior, and to analyze the mediating role of cognitive resistance and the moderating role of social class.

There is a U-shaped relationship between the degree of humanization of service machines and user misbehavior; Social class not only regulates the main effect of anthropomorphism on misbehavior, but also regulates the intermediary effect of anthropomorphism on cognitive resistance, thus affecting misbehavior.

The design of the service robot can be from the user’s point of view, combined with the user’s social class, match different user types, and provide the same preferences as the user’s humanoid service robot.

This study is an important reference value for enterprises and governments to provide intelligent services in public places. It can prevent the robot from being vandalized and also provide users with a comfortable human-computer interaction experience, expanding the positive effects of providing smart services by government and enterprises.

This study avoids and reduces users' misbehavior towards intelligent service robots, improves users' satisfaction in using service robots, and avoids service robots being damaged, resulting in waste of government, enterprise and social resources.

From the perspective of product factors to identify the inducing factors of improper behavior, from the perspective of social class of users to analyze the moderating effect of humanization degree and user improper behavior.