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What is the future of work going to look like? The aim of this paper is to show how the sociology of expectations (SE) – which deals with the power of visions – can make important contributions in terms of thinking about this issue by critically evaluating the dominant expert positions related to the future-of-employment- and artificial intelligence (AI) debate.

After providing a literature review regarding SE, an approach based on the latter is applied to interpret the dominant ideal-type expert positions in the future of work debate to illustrate the value of this perspective.

Dominant future scripts can be characterized by a focus on the effects of AI technology that give agency to technology and to the future, involve the hype of expectations with polarized frames, and obscure uncertainty. It is argued that these expectations can have significant consequences. They contribute to the closing off of alternative pathways to the future by making some conversations possible, while hindering others. In order to advance understanding, more sophisticated theorizing is needed which goes beyond these positions and which takes uncertainty and the mutual shaping of technology and society into account – including the role expectations play.

The study asserts that the dominant positions contain problematic assumptions. It makes suggestions for helping move beyond these current framings of the debate theoretically. It also argues that scenario building and backcasting are two tools that could help move forward thinking about the future of work – especially if this is done in a way so as to build strongly on SE.

The arguments presented herein enhance sense-making in relation to the future-of-work debate, and can contribute to policy development.

There is a lack of adequate exploration of the role of visions related to AI and their consequences. This paper attempts to address this gap by applying an SE approach and emphasizing the performative force of visions.

This study aims to investigate consumers’ intention to use onsite restaurant interactive self-service technology (ORISST) using a modified value attitude-behavior model. To extend the understanding of how consumers’ dining value focus could influence their intention to use ORISST, this study examines the conditional indirect effects of restaurant type (quick-service vs fine-dining) within the proposed model.

An online survey was developed and distributed to randomly selected respondents in the USA. A total of 588 (quick-service: 295; fine-dining: 293) responses were used for the data analysis. Structural equation modeling with a robust maximum likelihood method was used to examine the proposed model. To investigate the moderated effects of restaurant type, a latent moderated mediation model was used.

The results showed that consumers’ value perceptions toward technology use in restaurants influenced their intention to use ORISST via both hedonic and utilitarian expectations. Latent moderated mediation analyzes revealed that the mediation effect of hedonic expectation between perceived value and the intention was stronger in fine-dining than in quick-service restaurants.

This study extends the understanding of consumer intentions to use interactive self-service technology in restaurants by building on a model that is customer-oriented instead of tech-specific. Furthermore, the conditional effects of restaurant type are investigated using the latent moderated structural equation method. The findings of this study provide guidelines for managers of quick-service and fine-dining restaurants to better incorporate ORISST in their restaurants, to boost customer experiences and to increase operational efficiency.

This paper aims to understand an emerging paradigm for business-to-business selling, Sales 2.0, which connects various enabling technologies within leading sales processes to drive improved business and relational outcomes. In the context of Sales 2.0, this paper addresses the need for buyer–seller dyadic sales research in the literature and highlights the importance of understanding buyer and seller perspectives regarding technology expectations and relationship-building performance.

This research utilizes a dyadic (salesperson–customer) data collection methodology, involving 74 matched salesperson and customer responses (37 dyads) to an online survey. Existing salesperson (self-report) measures of customer technology expectations and relationship-building performance with customers were utilized and adapted to provide dyadic measures to test for buyer–seller perceptual differences.

The dyadic data analysis supports the presence of significant perceptual differences between the salesperson and their customer, respective of customer technology expectations and relationship-building performance measures. In particular, the analysis reveals bidirectional perceptual differences for the two measures, whereas the salesperson underestimates the importance of their customer’s technology expectations, but overestimates their relational performance relative to their customers.

As technology continues to transform salesperson interactions with customers, the value of capturing a deeper understanding about those interactions increases. This study uses matched salesperson–customer dyads from a health-care sales organization to provide researchers and practitioners with insightful findings with respect to buyer–seller interactions and perceptual differences. Further, the research uniquely advances dyadic measures of customer technology expectations and relationship-building performance with customers to advance sales research in the context of Sales 2.0.

This study contributes to the limited and rather fragmented research on mobile payment (m-payment) within a post-adoption context by identifying individual characteristics (personal innovativeness and m-payment self-efficacy) and m-payment quality characteristics (system quality, information quality and service quality) that can influence expectations about performance and effort of this technology. These two outcome expectations may affect user satisfaction with m-payment, which will in turn influence users' continued intention to use this technology.

A survey was carried out among university students in the United Arab Emirates who have used the m-payment method. Structural equation modeling technique was used to test and analyze both the measurement model and the structural model.

Individual characteristics are important in establishing users' expectations of the ease of use and usefulness of m-payment. However, of the quality characteristics, only system quality significantly affected users' expectations of the ease of use and usefulness of m-payment.

The findings of this study provide unique insights into the individual and quality characteristics that will eventually lead to continued intention to use m-payment. This will help businesses to develop appropriate marketing strategies to increase adoption and use of m-payment.

Drawing broadly from the technology frame (Davidson, 2002) and organizing vision perspectives (Swanson and Ramiller, 1997) which consider the business value of information technology as resulting from actors' efforts to make sense of new technology, the study applies Ojala's (2016) business model framework to examine how different sets of actors understand the value of blockchain within the healthcare sector.

To include the perspective of different sets of actors, the research combines a systematic literature review to capture academic research, semi-structured interviews with blockchain experts, with an analysis of blockchain healthcare vendors.

The study finds a high degree of congruence between the perspective of different actors, with key sources of blockchain value concentrated around value proposition, particularly enhancing privacy and security; value capture, specifically cost savings, and value network, mostly enhancing data accessibility and reducing intermediation. Value delivery is the least emphasized value creation mechanism and concerns primarily improvements in supply chain transparency. Minor variations between actors' interpretations of value exist, mostly around the contribution of blockchain to support the value proposition and include the provision of social value, the creation of trust, supporting automation and improving employment.

Recognizing that the value of new technology is as much the result of actors' interpretations, as the objective outcome of its deployment, this study takes a multi-stakeholder perspective to examine blockchain's business value and highlights new aspects of value associated with blockchain deployments. The findings include a value outcome framework that allows systematic comparisons between blockchain implementations across contexts.

The long-term success of internet banking (IB) services is connected with continuous use. Therefore, examining factors which influence IB user continuance intention is important. Grounded in technology continuance theory, bank transparency and task technology fit (TTF) model, the purpose of this study is to develop a unified technology continuance model to investigate IB user continuance intention.

The research model was empirically tested with 348 responses. Respondents included in this study had prior experience with IB services. For hypotheses testing, the structural equation modelling approach was used.

Findings indicate that the research model has substantial power in explaining IB user continuance intention. Importance performance matrix analysis revealed that bank transparency had the highest importance in determining IB user continuance intention. Therefore, factors like user satisfaction and perceived usefulness have shown a medium level of importance in determining IB user continuance intention. Satisfaction is influenced by perceived usefulness and confirmation and established a significant impact on IB user continuance intention.

The findings of this research are useful for bank managers and policymakers to develop and design IB services according to user’s expectations. Results demonstrate that expectation confirmation and perceived usefulness are antecedents of IB user satisfaction and IB user continuance intention. In addition to that bank, transparency has shown a significant effect on user expectation and IB user continuance intention. These findings established that accuracy in sharing bank information and clarity in transaction charges encourage the user to continue the use of IB services.

The current study develops a unified technology continuance model based on the TTF model and technology continuance theory and investigates IB user continuance intention. Moreover, bank transparency is added in the technology continuance model and established a significant impact towards user expectation confirmation and continuance intention. These findings contribute to the limited body of research in the context of IB user continuance intention and enrich information system literature.

This study aims to investigates customer satisfaction from the use of bank chatbots and the effect of perceived trust in chatbots and banks' reputation on customer satisfaction.

A survey is conducted in Turkey involving 240 customers who experienced banking transactions using a chatbot. Partial least squares structural equation modeling (PLS-SEM) is used to investigate the relationships between the variables. The data were analyzed using SPSS 21 and SmartPLS programs.

Perceived performance, perceived trust and corporate reputation significantly affect customer satisfaction with chatbot use. Customer expectations and confirmation of customer expectations have no direct impact on customer satisfaction, but customer expectations positively affect perceived performance. Customer expectations exert an indirect influence on customer satisfaction through perceived performance. Perceived performance has a positive impact on the confirmation of customer expectations, but customer expectations do not significantly impact the confirmation of customer expectations.

This study relies on a limited number of participants. Moreover, its sample is not representative of the target population due to the convenience sampling technique. Even if the results may not be generalized to the entire population of Turkey, they reflect the reality of emerging markets with relatively high technology sensitivity and a young population.

The results provide new insights regarding banking service delivery channels, which may be of interest to professionals, academics, banks' top management, product development teams, design teams and customer satisfaction units.

This study is believed to help the community make their lives easier by providing them with knowledge and awareness about chatbots.

This study extends expectations confirmation theory's predictions to chatbot use in banking.

Studies show that discourses are important in legitimating emerging fields. However, we still lack understanding of how potential participants’ interpretations of discourses shape their involvement in emerging fields – particularly when the field’s definition is ambiguous. Drawing on an in-depth study of the emerging nanotechnology field we show that individuals’ affective responses to discourses play an important role in their decisions to participate. We find that discourse, expectations, affective responses, and participation in emerging fields are mutually constituted, and develop a model that shows these interconnections. Theoretically, our study expands understandings of discourse and field emergence by incorporating affect.

This study focuses on memorable customer shopping experience design in the sporting goods retail setting. It aims to identify the phygital customers' needs and expectations that are satisfied through in-store technologies and to detect the in-store strategies that use these technologies to make the store attractive and experiential.

This exploratory study adopted a qualitative research methodology, specifically a multiple-case study, by performing semi-structured interviews with sporting goods store managers.

Sporting goods retailers use various in-store technologies to create a phygital customer shopping experience, including devices, mobile apps, wireless communication technologies, in-store activations, support devices, intelligent stations, and sensors. To improve the phygital customer journey and the phygital shopping experience, retailers meet customers' needs for utilitarian, hedonic, social, and playfulness experiences. Purely physical or digital strategies, as well as phygital strategies, are identified. This research also proposes a model of in-store phygital customer shopping experience design for sporting goods retailers.

Sporting goods managers can invest in multiple technologies by designing a physical environment according to the customers' needs for utilitarian, hedonic, social, and playful experiences. In addition, they can improve the phygital customer shopping experience with specific push strategies that increase customer engagement and, in turn, brand and store loyalty.

This study highlights how the phygital customer experiential journey can be created through new technologies and improved with specific reference to the sporting goods stores.

Based on the post-acceptance model of information system continuance (PAMISC), this study investigates the influence of the early-stage users' personal traits (specifically personal innovativeness and technology anxiety) and ex-post instrumentality perceptions (specifically price value, hedonic motivation, compatibility and perceived security) on social diffusion of smart technologies measured by the intention to recommend artificial intelligence-based voice assistant systems (AIVAS) to others.

Survey data from 400 US AIVAS users were collected and analyzed with Statistical Product and Service Solutions (SPSS) 18.0 and the partial least square technique using advanced analysis of composites (ADANCO) 2.1.

AIVAS technology is presently at the early stage of market penetration (about 25% of market penetration in the USA). A survey of AIVAS technology users reveals that personal innovativeness is directly and indirectly (through confirmation and continuance) associated with a stronger intention to recommend the use of the device to others. Confirmation is associated with all four ex-post instrumentality perceptions (hedonic motivation, compatibility, price value and perceived security). Among the four, however, only hedonic motivation and compatibility are significant predictors of satisfaction, which lead to use continuance and, eventually, intention to recommend. Finally, technology anxiety is found to be indirectly (but not directly) associated with a lower intention to recommend.

This is the first study conducted on the early-stage AIVAS users that evaluates the influence of both personal traits and ex-post instrumentality perceptions on users' intention for continuance and recommendation to others.