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The purpose of this paper is to identify the factors that explain the acceptance of self-service ordering systems (SOSs) for restaurants and to explore the effects of “self-service system service quality” (SSQ) and “interpersonal service quality” (ISQ) on the acceptance factors extended from the Unified Theory of Acceptance and Use of Technology model.

This study targets customers who have recently used SOSs to order foods in middle-class restaurants. In total, 402 valid survey samples were obtained. Partial least squares (PLS) analysis was used to examine the factors of user acceptance of using SOSs.

The results of the PLS-SEM analysis indicate that SSQ has a significant effect on accuracy expectancy, speed expectancy and effort expectancy; ISQ has a significant effect on accuracy expectancy, speed expectancy, effort expectancy and facilitating conditions; and accuracy expectancy, speed expectancy, effort expectancy, social influence, facilitating conditions and budget expectancy significantly influence user acceptance of SOSs. Furthermore, user experiences moderate the effect of speed expectancy and effort expectancy on user acceptance.

This study introduces three technology acceptance factors (accuracy, speed and budget) for researchers to consider in the future. It also extends the knowledge about the human service factor when middle-class restaurants adopt self-service technologies (SSTs). Recommendations are provided for system developers to improve the system quality of SSTs and service staff to rethink their roles in adopting SSTs in the service industry.

本文研究目的有:（1）确认解释客人接受餐厅自助订餐系统（SOSs）的决定因素（2）探索自助系统服务质量（SSQ）和人机服务质量（ISQ）对于UTAUT模型科技接受因素的作用。

本论文的目标受众为近期使用过SOSs在中等餐厅点餐过的客人。样本为402份有效问卷数据。本论文使用PLS分析检测用户接受SOSs的各项因素。

PLS-SEM分析结果表明, SSQ对准确预期、速度预期、努力预期, 有显著作用; ISQ对于准确预期、速度预期、努力预期、以及辅助条件, 有显著作用; 准确预期、速度预期、努力预期、社会影响、辅助条件、以及预算预期对于SOSs用户接受有显著作用。此外, 用户体验调节速度预期和努力预期对于用户接受的作用。

本论文新增了三种科技接受因子（准确度、速度、和预算）, 为未来的科研创造土壤。本论文还扩展了我们对于人员服务因子在中等餐厅采用SSTs的认知。本论文建议系统开发者应该提高SST系统质量, 以及建议服务人员重新审视在服务产业采用SST中自己的位置。

Employs the integral transform method in the hybrid numerical‐analytical solution of fully developed laminar flow within a class of irregularly shaped ducts, with respect to the co‐ordinate system chosen to represent the geometry under consideration. A quite general formulation of a two‐dimensional steady‐state diffusion problem is initially considered, and a formal solution is provided. The original partial differential equation is analytically transformed into an infinite system of ordinary differential equations for the transformed velocity field in the flow direction. On truncation to a sufficiently large finite order, adaptively chosen to meet prescribed accuracy requirements, well‐established numerical schemes for boundary value problems are utilized, readily available in scientific subroutines libraries. Illustrates convergence rates for a few typical duct geometries and critically examines previously reported numerical solutions.

Points out that customer satisfaction and retention are critical for retail banks, and investigates the major determinants of customer satisfaction and future intentions in the retail bank sector. Identifies the determinants which include service quality dimensions (e.g. getting it right the first time), service features (e.g. competitive interest rates), service problems, service recovery and products used. Finds, in particular, that service problems and the bank’s service recovery ability have a major impact on customer satisfaction and intentions to switch.

Many studies, motivated by concerns for activity-based costing (ABC) implementation efforts being less than successful, have suggested that the lack of success in this area stems more from behavioral, as opposed to technical, factors. This concern for the behavioral aspects of systems implementation has also emerged from much of the more general information systems research examining determinants of implementation success. Accordingly, the purpose of this study is to determine if a popular process theory of motivation, expectancy theory, would be useful in explaining the motivation of managers to incorporate ABC information into their job. Data obtained from two experiments employing a judgment modeling methodology support the relevance of both the valence and force models of expectancy theory in this context. Further, the judgments provided by the subject managers suggest they perceive improved product cost accuracy as the most beneficial outcome of ABC use, followed by an equivalent appreciation for both an enhanced ability to communicate the underlying economics of the firm and to identify non-value-added activities. Additionally, subject managers exhibited a greater concern for the possibility that obtaining the data to maintain the ABC system would be difficult and costly than they did for concerns that the ABC information would increase the level of complexity of the information that they use.

A great deal of work has been done by industrial and organisational psychologists to express the utility of validated employee selection systems. Much of this work has focused on methods for estimating economic utility, to show how many dollars can be gained or saved by implementing a new selection procedure. These methods can be quite useful, yet it is often difficult for the sponsors of selection systems to appreciate the credibility of the resulting dollar value estimates. Many users of selection systems still need to see utility analyses that demonstrate the selection system's value in more tangible behavioural terms that can be anchored in familiar performance metrics or standards of the organisation. This article presents all the information needed to compute theoretical expectancies for improvement of job performance under three well‐known models, eliminating the need to rely on incomplete expectancy tables. The methods described produce highly accurate results for all possible input values, and can be implemented easily using a variety of widely available software tools.

The purpose of this paper is to investigate the factors influencing Palestinian consumer attitudes toward artificial intelligence (AI)-powered online banking, focusing on performance expectancy, effort expectancy, social influence and facilitating conditions while considering the moderating role of trust in financial institutions.

To test the hypotheses, an empirical study with a questionnaire was carried out. The study was completed by 362 Palestinian customers who use online banking services.

The findings of this paper show that performance expectancy, effort expectancy, social influence and facilitating conditions significantly influence consumer attitudes toward AI-powered online banking. Furthermore, trust in financial institutions as a moderating variable strengthens the impact of performance expectancy, effort expectancy, social influence and facilitating conditions on consumer attitudes toward AI-powered online banking. Therefore, more studies should focus on certain fields and cultural contexts to get a more thorough grasp of the variables influencing adoption and acceptability.

The study's findings may be specific to the Palestinian context, limiting generalizability. The reliance on self-reported data and a cross-sectional design may constrain the establishment of causal relationships and the exploration of dynamic attitudes over time. In addition, external factors and technological advancements not captured in the study could influence Palestinian consumer attitudes toward AI-powered online banking.

Financial institutions can leverage the insights from this research to tailor their strategies for promoting AI-powered online banking, emphasizing factors like perceived security and ease of use. Efforts to build and maintain trust in financial institutions are crucial for fostering positive consumer attitudes toward AI technologies. Policymakers can use these findings to inform regulations and initiatives that support the responsible adoption of AI in the financial sector, ensuring a more widespread and effective implementation of these technologies.

This research delves into Palestinian consumer attitudes toward AI-powered online banking, focusing on trust in financial institutions. It aims to enrich literature by exploring this under-explored area with meticulous examination, robust methodology and insightful analysis. The study embarks on a novel journey into uncharted terrain, seeking to unearth unique insights that enrich the existing literature landscape. Its findings offer valuable insights for academia and practitioners, enhancing understanding of AI adoption in Palestine and guiding strategic decisions for financial institutions operating in the region.

The purpose of this paper is to investigate the determinants of behavioural intention and use behaviour towards social networking apps. Exogenous latent constructs, namely, performance expectancy, effort expectancy and social influence are the key antecedents proposed based on the unified theory of acceptance and use of technology to predict the usage intention and behaviour of social networking apps (i.e. endogenous latent constructs). Experience as a moderator is the extended construct to explain social networking apps user’s behavioural intention.

To target young generation (Millennial), a cross-sectional data collection approach was conducted to collect data from the social networking apps users (i.e. Facebook, WhatsApp, WeChat, Twitter, Instagram, YouTube, Snapchat and others) whereby a total of 384 valid questionnaires were obtained from six universities in Malaysia. Statistical analysis using partial least squares path modelling approach and a variance-based structural equation modelling (VB-SEM) techniques is performed to analyse the measurement and structural relationship.

The findings indicate that performance expectancy, effort expectancy and social influence determine behavioural intention, and behavioural intention impacts social networking apps use behaviour. Moreover, the moderation analysis reveals that the relationship between effort expectancy and behavioural intention is moderated by experience, whereas the relationship between social influence and behavioural intention is not moderated by experience.

While the surge of social networking apps has gained tremendous popularity among Millennial as an attractive market segment, previous studies mainly have focussed on intention and behaviour of online users in general. Despite apps and related technologies which have opened a new era of effective communications in marketing, social networking apps usage intention and behaviour focussing on Millennial is not well understood in the current literature. This study contributes and sheds lights on the current issue of social networking apps usage intention and behaviour and looks into a key rising market segment, the Millennial users.

The purpose of this paper is to identify the factors affecting continuance usage of mobile payment.

Based on the valid responses collected from a survey questionnaire, structural equation modeling (SEM) technology was employed to examine the research model.

The results indicated that performance expectancy, trust in mobile payment and flow affect continuance usage. Among them, flow has a relatively larger effect. In addition, system quality has strong effects on performance expectancy and flow.

This research is conducted in China, where mobile internet is still in its early stage. Thus, the results need to be generalized to other countries that have developed mobile internet.

Extant research has mainly focussed on the effects of instrumental beliefs such as perceived usefulness on mobile payment user behavior, and has seldom considered the effect of flow experience. This research tries to fill the gap.

This study tests the expectancy disconfirmation model using survey data from citizens who recently had police encounters. We find support for the expectancy disconfirmation model’s primary hypothesis that increased disparity between expectations of police performance and actual service inversely affects citizen satisfaction with the way the police handle encounters. This finding persists for both voluntary (e.g. breaking and entering victims) and involuntary (e.g. traffic citations) police encounters. Our results also suggest that the scope of the expectancy disconfirmation model is limited. For example, the disparity between expectations and actual service is not correlated with citizen satisfaction with the police in general. Overall, the results show that the expectancy disconfirmation model is useful in that it provides conceptual guidance in an area of research that has been relatively void of theory, and can also help identify needed changes in police practices.