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This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context.

Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users.

The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively.

This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.

1. The study investigates customers' adoption of AI chatbots' recommendation.

2. The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

3. The central and peripheral cues are generalized according to cooperative principle theory.

4. Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

5. Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

6. Customers' mind perception positively moderates the central and peripheral paths.

The study investigates customers' adoption of AI chatbots' recommendation.

The authors develop research model based on ELM theory to reveal central and peripheral cues and paths.

The central and peripheral cues are generalized according to cooperative principle theory.

Central cues include recommendation reliability and accuracy, and peripheral cues include human-like empathy and recommendation choice.

Central and peripheral cues affect customers' adoption to recommendation through trust in AI.

Customers' mind perception positively moderates the central and peripheral paths.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

I test empirically the hypothesis that the monitoring role of the board of directors depends on the severity of the agency problems and the amount of information needed to monitor. I show that in high growth firms, where the agency conflicts are low and managers are likely to reveal more information to get advice, boards are more independent but less likely to monitor, while in low growth firms, boards are less likely to be independent, but the relationship between firm value and board independence is strong. Overall, boards become more independent but monitor less as firms’ growth opportunities increase, suggesting that managers trade off the amount of information released to the board to get a better advice and to mitigate the monitoring role of the board.

Are the explanations that companies provide when deviating from two board structure-related best practices under the Australian Stock Exchange’s “If not, why not” regulatory regime systematically influenced by company characteristics?

Multinomial logistic regressions are performed on a sample of 258 ASX-listed firms in the period 2004-2007. The dependent variable is the level of response to the “why not” pillar of the regime which requires companies to provide an explanation where they deviate from the recommended governance practice or practices. The variable is categorised into three levels: zero response, inadequate explanation and adequate explanation. This variable takes on a fourth possible level (full compliance) if both pillars of the regime are considered jointly. The independent variables are company size, ownership concentration, profitability, liquidity, age and the market-to-book ratio.

The regime appears to be well specified, but size is positively correlated to the quality of explanations given for the deviation. Other company characteristics have no important systematic effect.

Small firms, while availing of the regulatory flexibility that enables them to adopt governance systems that suit their corporate governance requirements, tend not to meet the reporting requirements that go with that flexibility.

To the best of the authors’ knowledge, this paper is one of the first to explore the justifications given for deviations from full compliance in the “if not why not” regime and covers new ground with respect to explanations given for non-adoption of board structure recommendations.

The purpose of this paper is to describe the Bree Collaborative’s background, history, structure, and work.

The Bree Collaborative was established by the Washington State Legislature to convene public and private health care stakeholders with the goal of identifying specific mechanisms to improve health care quality, outcomes, and affordability. These members are appointed by the Washington State Governor and represent public health care purchasers for Washington State, private health care purchasers (employers and union trusts), health plans, physicians and other health care providers, hospitals, and quality improvement organizations. Members annually select health care services that show high variation in care delivery, that are highly utilized without leading to better care or patient health, or that have known or suspected patient safety issues and develop recommendations for health care improvement.

Recommendations are meant to be implemented by the Washington State Health Care Authority and used to set a community standard across the state. Successful implementation depends on several factors including engaged health care purchasers, support from diverse partners, and a health care community willing to put the patient at the center of care.

Bottom-up, collective action through the Bree Collaborative can help achieve the triple aim for Washington State and should be used as a model nationally and internationally.

e-Commerce recommenders have positive benefits both for consumers and the online stores using them. The focus of research in this topic has mostly been technical (e.g. design, type of recommenders, inputs, or outputs). However, a prior key question is what leads a consumer to use an e-vendor’s recommender. The consumer process of adoption and use of such recommenders involves subjective factors which need a psychological approach. This perspective has been neglected so far. The purpose of this paper is to discuss and validate an integrative model which adapts various theories and models – i.e. the original formulation of the technology acceptance model (TAM), the integrated trust-TAM model, and the theory of planned behavior (TPB) – in order to explain such a process.

The field study consisted of a simulated online shopping process undertaken by a valid sample of 300 internet users with a recommender at a real online store (Amazon). Many of the constructs’ measurement scales have been adapted from previously validated scales never before applied to this study’s context, and the authors have consequently rigorously validated them here too; this also constitutes one of the research’s valuable contributions. Detailed exploratory and confirmatory factor analyses are applied to assess the empirical validity of the model.

The model’s core structure and its relationships are proved to be valid for explaining a consumer’s intention to use an e-vendor’s recommender In particular, trust and perceived usefulness of the recommender stand out as the determining factors of its use, though the consumer’s attitude toward the recommender and others’ opinion of its use also have significant influence too.

The consumer’s psychological angle has been overlooked by previous studies on the adoption and use of online stores’ recommendation systems. To the best of the knowledge, this is the first attempt to validate a model aimed at comprehensively approaching the consumer’s adoption of an e-vendor’s recommender. The findings provide several theoretical contributions and implications for practitioners.

Adoption of solar energy plays an important role in the growth of a country. There are many factors which influence the adoption of solar energy in India. The study is designed to identify factors that determine the acceptance or rejection of solar energy systems in India.

Relationship among identified variables is established through interpretive structural modelling (ISM) and thus a conceptually validated model is evolved. Further, MICMAC analysis is conducted to understand the driving power and dependence of these variables.

It is revealed that experience and habit, awareness and social influence are the intermediary variables. MICMAC Analysis shows that no variable is disconnected from the system and all the variables influence the adoption of solar energy in India.

The present study is expected to be useful to decision makers, end users and research organisations related to solar energy adoption.

Various intentional factors influencing solar energy systems adoption have been acknowledged in the present study, thus making it useful for formulation of action plans and enhance the usage of solar energy systems to improve environment quality.

The purpose of this article is to explain under what circumstances firm-level adoption of codes of good corporate governance will more likely be superficial rather than substantive in nature. The article contains lessons for any agency or country that attempts to implement deep and lasting changes in corporate governance via codes of good corporate governance.

The article reviews the literature on compliance with codes of good corporate governance and develops a conceptual model to explain why some firms that have formally adopted a code of good governance decouple this policy from its actual use.

Decoupling in response to the issuance of codes of good corporate governance will be more attractive to firms and also more sustainable under the following conditions: firms’ compliance costs are relatively high firms’ costs of outright and visible non-compliance are relatively high and outsiders’ compliance monitoring costs are relatively high.

The article contributes to the debate on compliance and convergence and provides policymakers with a conceptual framework for assessing the likelihood of successful regulatory change in corporate governance.

The purpose of this paper is to evaluate how the intermediation of an online agent in the relationship between prospective clients and professional service providers affects individual purchasing processes and decisions, and satisfaction with the professional service provider once the commercial transaction is concluded.

Drawing on the integrated trust-technology acceptance model, modified to include two additional variables to take into account of the specificities of the context investigated – users’ perceived reduction of information asymmetry and satisfaction with the professional service provider – a research framework is developed and tested with a research design combining a decision tree procedure with structural equation modelling and multi-group analysis. Participants are 188 users of an Italian website which incorporates an online agent that refers notaries to prospective clients.

Decisions to purchase professional services brokered by online agents depend upon trust in the agent, and users’ perceptions of the agent’s ability to reduce information asymmetry, as well as its perceived usefulness. Online agents for professional services can be effective as well as efficient: users who bought the service from an agent-referred notary had higher levels of satisfaction with their professional service provider than users who purchased the service from a different notary.

This is the first empirical effort to investigate the effects of online agents in the specific context of professional service purchasing. The uniqueness of the research context permitted identification of a new type of online agent, the “double-sided online referral agent”.