Breaking into the black box of customer perception towards robot service: Empirical evidence from service sector

The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained R2 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies

Determinants of Remuneration Committee Chairman’s Pay: Evidence from the UK

This study investigates the association between the compensation of Remuneration Committee Chairpersons (RCCs) and their characteristics. Utilizing data from firms listed on the UK FTSE350 index between 2010 and 2020, the research unveils that RCC remuneration is influenced by factors such as observable efforts, time commitment, and accumulated experience. Notably, the analysis reveals a substantial gender gap in RCCs’ pay. The results suggest that the contractual pricing of individual director-level attributes plays a role in explaining disparities in compensation for roles with similar responsibilities. Furthermore, the study sheds light on the intricate process of determining compensation within the directorial hierarchy. It delves into how differences in pay among individuals occupying similar positions across various companies can be elucidated by the distinct attributes and qualifications of each individual. Ultimately, the findings advocate for a nuanced examination of directorial roles, highlighting the necessity of distinguishing between different director roles rather than treating them as a homogeneous entity

The Impact of Artificial Intelligence Disclosure on Financial Performance

This study determines to what extent Jordanian banks refer to and use artificial intelligence (AI) technologies in their operation process and examines the impact of AI-related terms disclosure on financial performance. Content analysis is used to analyze the spread of AI and related information in the annual report textual data. Based on content analysis and regression analysis of data from 115 annual reports for 15 Jordanian banks listed in the Amman Stock Exchange for the period 2014 to 2021, the study reveals a consistent increase in the mention of AI-related terms disclosure since 2014. However, the level of AI-related disclosure remains weak for some banks, suggesting that Jordanian banks are still in the early stages of adopting and implementing AI technologies. The results indicate that AI-related keywords disclosure has an influence on banks’ financial performance. AI has a positive effect on accounting performance in terms of ROA and ROE and a negative impact on total expenses, which supports the dominant view that AI improves revenue and reduces cost and is also consistent with past literature findings. This study contributes to the growing body of AI literature, specifically the literature on AI voluntary disclosure, in several aspects. First, it provides an objective measure of the uses of AI by formulating an AI disclosure index that captures the status of AI adoption in practice. Second, it provides insights into the relationship between AI disclosure and financial performance. Third, it supports policymakers’, international authorities’, and supervisory organizations’ efforts to address AI disclosure issues and highlights the need for disclosure guidance requirements. Finally, it provides a contribution to banking sector practitioners who are transforming their operations using AI mechanisms and supports the need for more AI disclosure and informed decision making in a manner that aligns with the objectives of financial institutions

Australian board composition and performance: Meta-analysis and implications for governance research

This paper aims to inform the ongoing emphasis on board structure (Yu, 2023) by reconciling the Australian empirical evidence on firm performance-board structure links. While international findings are instructional, differences between governance systems across nations (Alabdullah et al., 2022; Outa &amp; Kutubi, 2021) highlight the importance of understanding the salient nature of the Australian context compared to the UK and US (e.g., fewer listed companies with lower levels of institutional shareholding, higher agency costs and higher compliance to the prescribed governance practices. Meta-analysis was employed to reach an overall Pearson correlation for the association between firm performance and four board composition characteristics (i.e., board independence, CEO duality, board size, and female ratio on boards). The meta-analysis employed includes all empirical studies that used Australian data to investigate firm performance-board structure links. This research also provides guidance on improved theorizing, measurement, and modelling for boards’ research. The results indicate that the correlation between each board’s independence, CEO duality, and financial performance is almost zero. Moreover, board size and female ratio on board have a small positive correlation with financial performance. This paper highlights the importance of considering a specific theory and evidence before employing intermediary variables as controls.</p