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This study examines how chatbots could improve the client experience in the banking sector. Due to their quick and effective customer service, chatbots are becoming more and more popular, but it is still unknown whether they can improve the customer experience. In order to gather data from a simple random sample of Palestinian banking clients in the Gaza Strip, a survey was conducted utilizing the explanatory technique. To test hypotheses, data collected from 337 individuals was evaluated using simple regression analysis. According to the results, chatbots may enhance the customer experience by offering 24/7 availability, prompt support, and customized replies. However, issues with data privacy, lack of human interaction, and chatbot accuracy were also noted. The study comes to the conclusion that chatbots may be an effective tool for increasing customer experience in the banking sector, but their design, deployment, and interaction with current customer service channels must be carefully considered. This study significantly adds to the body of knowledge on chatbots and their potential influence on customer experience. The study offers useful insights into the particular difficulties and potential of employing chatbots in a highly regulated and customer-focused industry by concentrating exclusively on the banking sector. The results show that chatbot implementation in banking needs to be approached thoughtfully and strategically to maximize their potential for improving customer experience while limiting any possible downsides.

This study aims to understand a customer-purchase mechanism in the artificial intelligence (AI)-powered chatbot context based on the elaboration likelihood model (ELM) and technology acceptance model (TAM). The first objective is to examine how to boost chatbot adoption. The second objective is to investigate the role of information characteristics, technology-related characteristics and attitude toward AI in purchase intention.

Data was collected from a sample of 492 users in Vietnam, who are potential customers of chatbots for purchase. Structural equation modeling was applied for data analysis.

Results illustrate that chatbot adoption is significantly influenced by information credibility, technology-related factors (i.e. interactivity, relative advantage and perceived intelligence), attitude toward AI and perceived usefulness. Moreover, information quality and persuasiveness motivate information credibility. Information credibility and attitude toward AI are the essential motivations for perceived usefulness. Finally, chatbot adoption and information credibility determine purchase intention.

The results are insightful for practitioners to envisage the importance of chatbot use for customer purchase in the AI scenario. Additionally, this research offers a framework to practitioners for shaping customer engagement in chatbots.

The value of this work lies in the incorporation of technology-related characteristics into the two well-established theories, the ELM and TAM, to identify the importance of AI and its applications (i.e. chatbots) for purchase and to understand the formation of perceived usefulness and chatbot use through information credibility and attitude toward AI.

This paper aims to focus on the effect of the operating condition such as the impeller speed on the centrifugal fan performance and flow characteristics. The ability to predict the behavior of the airflow motion in a centrifugal blower is essential for obtaining the topology optimization design.

A physical model of the air blower consisting of these main parts in a blower system: collector, impeller, outlet flange and volute casing, and the appropriate boundary conditions are set up by ANSYS software. Computation fluid dynamics are performed for the numerical analysis. The calculation of blower performance parameters such as total pressure, efficiency and flow rate is based on the Reynolds averaged Navier–Stokes equations and k-εturbulence flow model.

The numerical results show that the change in operating conditions has a significant effect on the blower performance, and the pressure maintained inside the blower is higher for a larger impeller rotational speed.

This work is original and has not yet been submitted to elsewhere or published previously.

This paper aims to investigate empirically the impact of economic policy uncertainty (EPU) on small-to-medium enterprises’ (SMEs) investment efficiency and whether product market competition influences this association.

The study was conducted on French SMEs listed on the “CAC Mid & Small” Index over 2008–2021. This paper proposes a quantitative approach to test the relationship between the EPU and SME investment efficiency.

These findings show that EPU significantly alleviates SMEs’ investment inefficiency, reflected in the reduction of overinvestment and underinvestment. As EPU increases, firms with more exposure to such uncertainty invest more efficiently, and their overinvestment tendency becomes lower, while reducing the risk of underinvestment. These results are still significant after a series of robustness checks. Further analysis shows that EPU mitigates investment inefficiency to a greater extent for firms operating in highly competitive industries, and better information environments.

This study was limited to the French EPU index and could be extended to a European or even international scale. Moreover, using alternative uncertainty indexes across various European countries can be more advantageous in further studies. Although results suggest that EPU affects investment efficiency, future studies could further explore the mechanisms through which EPU affects SMEs’ investment efficiency and, in particular, across different industries. Understanding these variations due to the specific industry-EPU sensitivity can provide valuable insights. Finally, it would be interesting to examine the risk management strategies adopted by SMEs in the face of EPU, combined with other growing risks, such as climate risk.

In the face of high EPU, SME managers must improve risk management, adopt appropriate investment strategies, consider using predictive analytics or economic forecasting tools and embrace technology and innovation that enhance agility and responsiveness to policy uncertainty. Besides, political decision-makers should adapt their regulatory policies (tax, labor, housing, etc.) to preserve the efficiency of SME investment.

Although the debates on how policy uncertainty affects the investment and financing of large businesses have received a great concern of academia, to the best of the authors’ knowledge, this is the first study that focuses on the effect of EPU on investment distortions for SMEs.

AI-based chatbots are revamping employee communication in organizations. This paper examines the adoption of AI-based employee experience chatbots by employees.

The proposed model is developed using behavioral reasoning theory and empirically validated by surveying 1,130 employees and data was analyzed with PLS-SEM.

This research presents the “reasons for” and “reasons against” for the acceptance of AI-based employee experience chatbots. The “reasons for” are – personalization, interactivity, perceived intelligence and perceived anthropomorphism and the “reasons against” are perceived risk, language barrier and technological anxiety. It is found that “reasons for” have a positive association with attitude and adoption intention and “reasons against” have a negative association. Employees' values for openness to change are positively associated with “reasons for” and do not affect attitude and “reasons against”.

This is the first study exploring employees' attitude and adoption intention toward AI-based EEX chatbots using behavioral reasoning theory.

Leveraging the technology acceptance model (TAM) and the stimulus–organism–response (S–O–R) theory, this paper aims to investigate how the utilitarian and hedonic factors in virtual reality (VR) technologies affect consumers' intention to travel in the endemic phase of COVID-19. At the same time, the study incorporated emotional engagement and two forms of trust as possible organisms for this model.

Through snowball sampling, data collected from 263 respondents were analysed using the partial least square structural equation modelling (PLS-SEM).

The findings revealed that among the different forms of hedonic and utilitarian factors, all but perceived entertainment has a significant positive relationship to emotional engagement. Additionally, emotional engagement positively influences trust in the product and seller. However, the results show that only trust in the seller has a significant relationship with travelling intention. Predictive analysis shows that the model displays a strong predictive power.

This study differentiates from the existing literature by investigating the effect of VR technologies on the two different forms of trust and emotional engagement on travelling intention. This study extends earlier studies by supplementing the explanatory perspective with a predictive focus, which is particularly important in making sound recommendations on managerial decision-making.

This paper aims to explore how open innovation communities contribute to the adoption of building information modelling (BIM) in the construction industry.

The paper presents a cross-case analysis of two construction communities, buildingSMART Norway and the BIM Vietnam Community. Data were collected based on 21 semi-structured interviews conducted with industry experts actively engaged in these two communities. The theoretical basis for the study was open innovation and the institutional intervention model, which delineates institutional actions related to the adoption of new information technology.

The findings show both similarities and differences in the way in which the communities contribute to industrial practice. Both communities use similar knowledge channels and repositories but apply different approaches to innovation creation and diffusion. In addition, trust can support BIM innovation in the community context.

The comparison of buildingSMART Norway and the BIM Vietnam Community in accelerating BIM innovation allows for exploring how open innovation communities support BIM adoption in the construction industry. The findings provide insights for construction communities into creating and diffusing BIM innovation. In addition, the examples of gaining benefits from community innovation activities are useful for construction firms and practitioners.

Under the background of continuous sluggishness of the real economy and expansion of asset sectors, the Chinese economy exists a trend of “from the real to the virtual.” Managing the corporate financialization is the key to prevent the real economy “from real to virtual.” The paper explores the influence of family involvement on corporate financialization since family firms are an important proportion of real sectors.

Based on Socioemotional Wealth Theory, this paper makes empirical study using the data of Chinese A-share listed companies from 2008 to 2022 to explore the influence of family involvement on corporate financialization, mainly from the perspectives of family engagement, family identity of CEO and family control power.

These are the findings: (1) Family engagement will inhibit corporate financialization; (2) Compared with employing external managers, family members acting as CEOs will decrease corporate financialization; (3) The proportion of family ownership is negatively correlated with the level of corporate financialization.

The originality of this paper include these: (1) Analyzing the differences in the financialization of real enterprises with different characteristics and attributes; (2) Expanding the research on the internal motivation of the financialization of the real enterprises, and supplementing the research literature on family firms and corporate financialization; (3) Exploring the internal influence mechanism of financialization of family firms under the background of Chinese culture.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

The objective of this research is to analyze how omnichannel consumer journey design (OCJD) influences the online customer experience (OCE) and e-satisfaction in consumers' multirooming behavior (searching for information in online and offline channels and purchasing the product online).

The problem-solving theory and experiential marketing perspective are the theoretical background that enables the establishment of five hypotheses. A survey is conducted on multiroomers who had purchased a product online, following an online and offline research journey.

The results showed that OCJD directly and indirectly (through online consumer experience) influences e-satisfaction. Females and younger individuals exhibited higher levels of e-satisfaction.

First, this research analyzes consumers' multichannel search strategies. Second, the consumer journey is incorporated into the study of multichannel retailing. Third, an emergent typology of cross-channel free-riding behavior is analyzed: multirooming.