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The purpose of this paper is to combine task-technology fit, theory of planned behaviour and individual technology optimism, and propose a better hybrid technology behavioural intention model to explain Taiwanese students’ usage behaviour for weblog learning.

A 31-item questionnaire with eight constructs was administered to undergraduate and graduate students enrolled in three universities in Taiwan. A total of 380 voluntary, usable responses were received, and a research model estimated using Smart PLS was used to interpret the structural relation results.

The results of the research model were analysed using a structural equation modelling approach to test six hypotheses and three moderating hypotheses; significant support were found for seven of them. Accordingly, this study considered the level of technology optimism as a moderator to explore whether it impacts perceived behavioural control, attitudes and social influences on behavioural intention related to weblog learning.

This research provides a better understanding of individual and system characteristics, as well as social factors regarding weblog learning system acceptance and intention.

Based on the E-Service Quality (E-SQ) model, this study investigates the effects of self-service technology (SST) quality attributes, specifically automated teller machines (ATMs), on customer satisfaction. The interaction effects of technological optimism on the abovementioned link are also examined. SST usage is conceptualized as a multidimensional construct that consists of five dimensions (reliability, security, convenience, functionality and responsiveness).

The data were collected through a survey of a sample of Malaysian participants who used cash-recycling ATMs. The proposed theoretical model was tested using partial least squares (PLS) structural equation modeling (SEM).

The results suggest that reliability, convenience, and functionality are critical factors that affect customer satisfaction in using ATMs. Technological optimism was found to weaken the relationship between reliability and customer satisfaction.

Considering the relative novelty of cash-recycling ATMs in the market, banks should ensure a smooth, error-free and accessible functioning of the system. Special attention has to be given to tech-savvy consumers whose higher level of optimism, with an increase of perceptions of reliability, may suppress their heighten sense of fulfillment. This customer group could be offered interactive digital engagement through mobile applications and social networking channels.

The E-SQ model is a helpful tool to understand the reasons underlying user satisfaction with cash-recycling ATMs. The results also contribute to the theoretical development of the E-SQ model through the integration of technological optimism as a contingent factor.

This study empirically examined consumer adoption attitudes and behaviors toward nonfungible tokens (NFTs). Findings indicate that consumer attitudes toward NFTs are influenced by perceived usefulness, reliability and profit expectancy and that strong attitudes are associated with purchase intentions. Additionally, the relationship between attitudes and purchase intentions was moderated by technology optimism.

The authors utilized a partial least squares (PLS) model to examine the hypotheses in this empirical analysis. Obtaining a sample of actual NFT holders or experienced users is challenging. A total of 105 individuals participated in the study as valid responders by answering the screening question in the questionnaire. The authors opted for the PLS model as a research approach due to the limited size of the consumer population in the NFT market.

This study discovered that the adoption of NFTs was affected by technical aspects such as usefulness and reliability and the potential for future asset growth. Furthermore, the degree of attitude-to-intention conversion varied based on optimism, an inherent characteristic.

This study offers valuable insights for NFT owners, content providers and trading firms. For the NFT market to expand, it must meet consumers' expectations for the desired content features and asset investment attributes. Additionally, customer targeting strategies should attract and appeal to technology enthusiasts with an optimistic outlook on technology.

The authors conducted an initial empirical analysis of actual NFT consumers, an area of research studied sparingly despite its significance.

The purpose of this paper is to incorporate an extended technology acceptance model (TAM) and examine how various factors comprehensively influence and determine consumers’ perceptions, attitude, and usage intention of 3D-printed apparel.

An online survey was designed using established measures and 1,002 participants were recruited.

All external variables were related. Beyond indirect influences, tech optimism still moderately influenced ease of use, but weakly influenced attitude; aesthetics still strongly influenced usefulness and attitude, but weakly influenced usage intention; performance still strongly influenced ease of use, usefulness, and attitude. In addition, only indirect influences came from tech optimism to usefulness and usage intention, aesthetics to ease of use, and performance to usage intention. The TAM relationships were mostly confirmed, except ease of use to usefulness. Usage intention was mostly determined by attitude, which was largely influenced by design, performance, and usefulness, and limitedly contributed by aesthetics and usefulness.

Participants’ response might be influenced by the provided materials of 3D-printed apparel.

The present study explicitly showed a complete picture about all possible influences among factors. Business managers can make strategies to meet consumers’ needs based on the current study without worrying about overlooking any possible effects.

The current study, for the first time, examined: consumers’ adoption intention of 3D-printed apparel, the relationships among external variables, and how external factors comprehensively influenced consumers’ perceptions, attitude, and usage intention.

The technology readiness and acceptance model were mostly employed as theoretical bases to analyze tourist behaviors of adoption of innovative technologies that are part of the smart tourism offer. This study attention now turns to the field of smart tourism human resource management and tries to establish a model to explain the relationship between general dimensions of personality with systematic specific dimensions toward ICT acceptance.

The authors adopted the TRAM model as a way to better understand and evaluate the causal relationships between the personality dimensions, factors of perception, attitudes and behavior of users regarding the acceptance and use of innovative technologies. Based on the empirical data of 478 employees operating in tourist organizations, travel agencies and hotels, the authors employed regression analysis as the basic method for examining the research hypotheses and causal relationships between variables in the presented model.

The analysis revealed that employees in the tourism sector are inclined to adopt new technology, and that technological readiness has an impact on attitudes and intentions toward the use of technologies. Moreover, the results show that the path between the dimensions of technological readiness and intention to use technologies is to a certain extent mediated through perceived ease of use and perceived usefulness.

This research is among the first empirical studies that examine technology readiness and adoption in the context of smart tourism development. Besides the findings extend the literature on the mediating effect of perceived usefulness and perceived ease of use between technology readiness index and technology acceptance behavior.

The automation of services is rapidly growing, led by sectors such as banking and financial investment. The growing number of investments managed by artificial intelligence (AI) suggests that this technology-based service will become increasingly popular. This study examines how customers' technology readiness and service awareness affect their intention to use analytical AI investment services.

Hypotheses were tested with a data set of 404 North American-based potential customers of robo-advisors. In addition to technology readiness dimensions, the potential customers' characteristics were included in the framework as moderating factors (age, gender and previous experience with financial investment services). A post-hoc analysis examined the roles of service awareness and the financial advisor's name (i.e., robo-advisor vs. AI-advisor).

The results indicated that customers' technological optimism increases, and insecurity decreases, their intention to use robo-advisors. Surprisingly, feelings of technological discomfort positively influenced robo-advisor adoption. This interesting finding challenges previous insights into technology adoption and value co-creation as analytical AI puts customers into a very passive role and reduces barriers to technology adoption. The research also analyzes how consumers become aware of robo-advisors, and how this influences their acceptance.

This is the first study to analyze the role of customers' technology readiness in the adoption of analytical AI. The authors link the findings to previous technology adoption and automated services' literature and provide specific managerial implications and avenues for further research.

The purpose of this paper is to focus on radio frequency identification (RFID) acceptance and examine three understudied drivers: a company's satisfaction with existing logistics technologies, its logistics technology readiness (technology optimism and technology innovativeness), and relationship hostage position. The proposed conceptual model also investigates the impacts of RFID acceptance and these three antecedents on the company's logistics performance.

Survey data were collected from the members of three professional associations in the USA. Structural equation modeling was used to test the proposed relationships.

According to the analysis results, a company's satisfaction with existing technology has negative impact on RFID acceptance, and technology readiness has positive impact on RFID acceptance. However, the relationship between a company's hostage position and RFID acceptance was found to be only partially significant. Also, the positive relationship between a company's RFID acceptance and its logistics performance is confirmed in this study. Furthermore, while a company's satisfaction with existing technology and technology innovativeness were found to be positively related to logistics performance, its technology optimism and hostage position were not significant related to its logistics performance.

This research confirms that a company's RFID acceptance is positively related to logistics performance. Therefore, even if a company is satisfied with its existing technologies, careful evaluation is warranted to determine if RFID as a new technology is needed to maintain the company's logistics performance in a dynamic environment. Also, this research suggests that supply chain members should be extremely cautious about the power usage toward its partners, because the authors' results show that forcing other partners to take cooperative actions may not yield the desired results.

This is first study examining RFID technology through a behavioral perspective. A new construct, RFID acceptance, was proposed, and related measurement scale was developed and tested along with its antecedents and outcomes.

This research clarifies the connotations and dimensions of artificial intelligence (AI) technology stimulation and establishes a stimulus scale to explain the relationship between AI technology stimuli and smart customer experience.

This is an empirical study that uses SPSS 24.0 software to perform hypothesis testing on the path relationships between model elements.

Two dimensions of AI technology stimuli (i.e. passion and usability) have a significant, positive impact on smart customer experience; the moderating effects of contrasting dimensions of technology readiness (i.e. optimism and discomfort) are significantly different; smart customer experience has a significant, positive impact on the word-of-mouth (WOM) intentions of consumers.

There are several limitations. Most importantly, the data collected in this study are only from consumers who use intelligent customer service robots in the catering industry. Future research can consider exploring relevant AI technologies in other sectors.

This study has several implications that guide catering companies to develop various positioning and strategies for remaining competitive effectively.

Based on arousal theory, customer experience theory and WOM marketing theory, this is the first novel research project that empirically discusses the dimensions of AI technology stimuli, smart customer experience and WOM intentions with regard to the moderating effect of the technology readiness of consumers toward AI technology.

This paper aims to establish and empirically investigate a research model examining the effect of four dimensions of the technology readiness index – optimism, innovativeness, discomfort and insecurity – on customer engagement that further influences purchase intention in the context of online shopping through artificial intelligence voice assistants (AI VAs).

Data were collected in India from 429 customers in a self-administered online survey. Data analysis uses the structural equation modelling technique.

Technology readiness dimensions, e.g. optimism, innovativeness, discomfort and insecurity, are critical factors driving customer engagement. Customer engagement further results in purchase intention in online shopping through AI VAs.

This study adds to the literature by understanding how customers’ technology readiness levels drive engagement and purchase intention. However, this study includes customer engagement as a unidimensional construct. Further research can consist of customer engagement as a multidimensional construct.

The findings offer guidelines for e-retailers to enhance customer engagement that matches their personality traits, thereby strengthening their purchase intention through AI VAs.

The research contributes to the literature by empirically investigating a research model, revealing optimism, innovativeness, discomfort and insecurity as crucial parameters for customer engagement and purchase intention.

The dominant worldview among marketers is one of technology optimism, which holds that technological advances influence consumers and businesses in positive ways. In direct contrast to this perspective, I advance the thesis that at the organizational frontlines where marketers interact with consumers by observing, informing, persuading, negotiating and co-creating with, and entertaining them, technology commonly produces unforeseen and unexpected effects on consumers with significant negative implications for marketers. The result is Adverse Technology-Consumer Interactions (ATCIs). Marketing practitioners play an instrumental role in producing and exacerbating ATCIs. Yet, I argue they have few incentives to fully investigate the underlying reasons, understand their scope, or find solutions to these potentially troublesome phenomena. Academic researchers, however, are uniquely poised to identify ATCIs, investigate them in depth by considering their industry-wide and society-wide import, develop appropriate theoretical frameworks, and design and test solutions to alleviate their effects. I develop these ideas by considering two ATCIs, falling response rates to customer surveys and customer reactance to frequent price changes. I also point out promising research opportunities for both these phenomena.