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Chatbots represent one of the most relevant trends within the communication settings and the management of relationships with consumers. New generations, such as millennials are favourable to interact with chatbots instead of human service assistants as they recognise the benefit linked to the technological advancements. Based on these premises, the paper intends to investigate what are the main factors affecting the quality of millennials–chatbots relationships and the new generations’ attitude and intention of using them within a specific industry such as the fashion one.

In order to achieve the aim, an online survey based on Likert-scale items from previous research has been implemented to test developed hypotheses. Construct reliability and discriminant validity of the hypothetical research model has been tested. Additionally, a partial least square analysis technique has been used with a bootstrapping technique for evaluating the significance level of path analysis.

A total of 191 responses have been collected. Most of millennials have familiarity with the concept of chatbot (52.4%). Perceived ease of use (PEOU) and perceived usefulness (PU) of chatbots positively influence the attitude towards using them by millennials. Attitude towards using chatbots positively influence the behavioural intention to use chatbots. Finally, also perceived trust and perceived risk affect the behavioural intention to use chatbots.

This study enriches the stream of research focused on investigating the acceptance of new technologies and their use for the development of high-quality relationships with customers. This study presents some limitations: the research model has been tested by using a convenient sample; then the study has been tailored for investigating millennials' perceptions in a specific industry; finally, the study focused on relational variables as determinants of using chatbots.

This study provides professionals operating in the fashion industry with practical and managerial insights relating to the perceptions collected among a precise customer cluster represented by millennials.

The paper investigates millennials' perceptions about chatbots within a specific industry related to the fashion system. Additionally, the paper explores at what extent relational variables such as trust and risk could affect the quality of millennials–chatbots relationship.

The purpose of this paper is to examine the pricing of vacant lots in master planned golf course communities (GCCs) over the period of 2000-2016. The authors compare the longitudinal pricing behavior of different lot types during this economic cycle and examine the causes of the property bubble and subsequent deterioration of the business model with the arrival of the Financial Economic Crisis (FEC).

The authors construct spatial hedonic models for three master planned GCCs in Pickens County, South Carolina and use interaction dummies to examine the pricing of different types of vacant lots before and after the FEC.

The authors find that there is a collapse in value for interior lots in the GCCs compared to interior lots in the county. As interior lots comprise over 50 percent of inventory in a typical master planned GCC, this loss of real estate value threatens the viability of such communities in the aftermath of the FEC.

The research results inform real estate investors, real estate developers, current homebuyers and potential homebuyers of the impacts of the FEC on master planned GCCs and some of the risks associated with such developments.

This is the first paper the authors are aware of that indicates the financial viability of master planned GCCs is associated with the pricing fragility of interior lots during cyclical markets. While demand for premium quality lots suffers, there is a collapse in demand for interior lots during the crisis.

Driven by Davis’s (1989) technology acceptance model (TAM) and Westaby’s (2005) behavioral reasoning theory (BRT), the purpose of this study is to develop and test a conceptual model and examine consumers’ acceptance of artificial intelligence (AI) chatbots for apparel shopping.

Data from 353 eligible US respondents was collected through a self-administered questionnaire distributed on Amazon Mechanical Turk, an online panel. Confirmatory factor analysis and path analysis were used to test all hypothesized relationships using the structural equation model.

The results show that optimism and relative advantage of “reasons for” dimensions have a positive and significant influence on perceived ease of use (PEU), while innovativeness and relative advantage have a positive and significant influence on perceived usefulness (PUF). Discomfort and insecurity have no significant impact on PEU and PUF. However, complexity has a negative and significant impact on PEU but not on PUF. Additionally, PEU has a positive influence on PUF. Both PEU and PUF have a positive and significant influence on consumers’ attitudes toward using AI chatbots, which, in turn, affects the intention to use AI chatbots for apparel shopping. Overall, this study identifies that optimism, innovativeness and relative advantage are enablers and good reasons to adopt AI chatbots. Complexity is a prohibitor, making it the only reason against adopting AI chatbots for apparel shopping.

This study contributes to the literature by integrating TAM and BRT to develop a research model to understand what “reasons for” and “reasons against” factors are enablers or prohibitors that significantly impact consumers’ attitude and intention to use AI chatbots for apparel shopping through PEU and PUF.

How do cognitive aspects influence the use/non-use of accounting information by the politicians? The purpose of this paper is to conceptualize and theorize the readiness to use and the actual use of accounting information in relation to the human and social agency involved.

Applying cognitive fit theory and social cognitive theory, the authors explain how cognition of accounting information producers and users relates to their tasks and their environment. Analyzing cognitive matching, the authors develop accounting information usefulness as a function of the cognitive match between the accounting information producers and users.

The theoretical findings posit that cognitive fit increases with the degree of matching between the cognition of accounting information producers and the cognition of accounting information users. The theory proposes that enriching and matching the various cognitive factors lead to formation of more aligned mental representations to govern the processes of accounting information production and use as a prerequisite for the accounting information usefulness.

By theorizing human cognition, behavior and learning, the authors seek to contribute to the explanation and prediction of accounting information use. Future research needs to empirically validate and/or further develop the propositions.

Practically, the conceptualization can be used to align individual and collective learning on both sides and to introduce information use audit as an instrument for supporting collective learning.

The theory of accounting information usefulness is the first attempt in public sector accounting literature to explain the relation of production and consumption of accounting information in relation to the cognition of the actors involved.