Factors affecting the behavioral intention to adopt mobile banking: An international comparison

Over the past decade, the markets for mobile and wireless services have been among the world's fastest-growing, especially in Asian countries, presenting financial institutions with significant opportunities to offer value-added services. Mobile banking has since emerged as a new channel enabling the banks to react strategically to changes in competitive forces and to enhance customer convenience.Based on Diffusion of Innovations (DOI) theory, the Technology Acceptance Model (TAM), the Decomposed Theory of Planned Behavior (DTPB) model, this study develops an integrated model to provide a fuller understanding of factors facilitating or impeding the adoption of mobile banking, focusing on consumers in Taiwan and Vietnam. While subjective norms had a significant effect on the intention to adopt, three attributes of mobile banking (compatibility, perceived usefulness, and perceived risk) were found to have indirect effects on intention to adopt mobile banking through attitude toward adoption for consumers in both Taiwan and Vietnam. Intention to adopt mobile banking was indirectly influenced by self-efficacy and facilitating conditions, and directly affected by perceived behavioral control in both nations. Some differences in intention to adopt mobile banking between Taiwanese and Vietnamese are also discussed. Based on the research findings, managerial implications for financial institutions and mobile service providers are discussed.     

Deep learning diffusion by infusion into preexisting technologies – Implications for users and society at large

Artificial Intelligence (AI) in the form of Deep Learning (DL) technology has diffused in the consumer domain in a unique way as compared to previous general-purpose technologies. DL has often spread by infusion, i.e., by being added to preexisting technologies that are already in use. We find that DL-algorithms for recommendations or ranking have been infused into all the 15 most popular mobile applications (apps) in the U.S. (as of May 2019). DL-infusion enables fast and vast diffusion. For example, when a DL-system was infused into YouTube, it almost immediately reached a third of the world's population. We argue that existing theories of innovation diffusion and adoption have limited relevance for DL-infusion, because it is a process that is driven by enterprises rather than individuals. We also discuss its social and ethical implications. First, consumers have a limited ability to detect and evaluate an infused technology. DL-infusion may thus help to explain why AI's presence in society has not been challenged by many. Second, the DL-providers are likely to face conflicts of interest, since consumer and supplier goals are not always aligned. Third, infusion is likely to be a particularly important diffusion process for DL-technologies as compared to other innovations, because they need large data sets to function well, which can be drawn from preexisting users. Related, it seems that larger technology companies comparatively benefit more from DL-infusion, because they already have many users. This suggests that the value drawn from DL is likely to follow a Matthew Effect of accumulated advantage online: many preexisting users provide a lot of behavioral data, which bring about better DL-driven features, which attract even more users, etc. Such a self-reinforcing process could limit the possibilities for new companies to compete. This way, the notion of DL-infusion may put light on the power shift that comes with the presence of AI in society.     

Understanding the Blockchain technology adoption in supply chains-Indian context

Blockchain technology (BT) is expected to bring a revolutionary paradigm shift in the manner the transactions are carried in the supply chains. BT provides better visibility and transparency by removing the disadvantages of trust related issues in a supply chain. In this paper, we advance the literature on BT and its adoption in the supply chain by developing, and statistically validating a model for understanding the user perceptions on BT adoption. The model is based on the integration of three adoption theories- technology acceptance model (TAM), technology readiness index (TRI) and the theory of planned behaviour (TPB). Based on a survey of 181 supply chain practitioners in India the proposed model was tested using structural equation modelling. The study found that the TRI constructs- Insecurity and discomfort have an insignificant effect on the perceived ease of use and usefulness. Perceived usefulness, attitude, and perceived behavioural control affect the behavioural intention. Subjective norm has a negligible impact on behavioural intention. This is one of the preliminary studies on BT adoption in supply chain and the findings imply that the supply chain practitioners perceive BT adoption free of efforts and would help them to derive maximum benefits for improving the supply chain effectiveness.     

Security factors on the intention to use mobile banking applications in the UK older generation (55+). A mixed-method study using modified UTAUT and MTAM - with perceived cyber security,risk, and trust

The convenience and accessibility of mobile banking applications has resulted in this becoming the preferred method of banking in the UK. Although popular amongst a younger generation, uptake is significantly lower among the older generation of those aged 55+, with some attributing this to cyber security and privacy concerns.This study proposes a model that can be used to measure the influence of cyber security factors on intention to use mobile banking applications, in the UK 55+. The unified theory of acceptance and use of technology (UTAUT) model was modified to include perceived cyber security risk, perceived cyber security trust, and perceived overall cyber security. Unlike similar studies which have been solely quantitative, this research brings further insight using a mixed-methods approach which harnesses both qualitative and quantitative data.The research model was tested using partial-least-squares structural equation modelling on coded questionnaire data, collected from 191 participants. Qualitative data was analysed through a thematic analysis. Both sets of data were analysed using a final convergent mixed-method. The results show that performance expectancy followed by perceived cyber security risk are the main determinants of intention to use mobile banking applications in the UK 55+.     

A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model (UTAUT)

Smart Farming is the application of modern technologies, tools and gadgets for increasing the agricultural crops quality and quantity. The Internet of Things (IoT) technology has had a prominent role in the establishment of smart farming. However, the application of this technology could be hard and, in some cases, challenging for the Middle Eastern users. Therefore, the research purpose is to identify the influential factors in the adoption and then application of IoT in smart farming by farmers with a contextualized approach in Iran, a typical Middle Eastern country. Thus, the Unified Theory of Acceptance and Use of Technology (UTAUT) has contextually been used as the theoretical model of the research. The results accentuated and proved the positive impacts of performance expectancy (H1), effort expectancy (H2), social influence (H3), individual factors (H4), and facilitating conditions (H5), on the intention to use IoT technology. Ultimately, the results were indicating the significant impact of behavioral intention on the actual usage of IoT technology (H6). One of the implications of the research is for the IT policymakers in the agricultural sector in the Middle East, where water and cultivable land are two valuable but scarce economic resources. Hence, smart farming could not be promoted unless the farmers had fulfilled its prerequisite factors proposed by the research results for using the IoT technology.     

Predicting the intention to use and hedonic motivation for mobile learning: A comparative study in two Middle Eastern countries

Drawing on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) Model, this study aimed to determine the key variables that facilitate the acceptance of mobile learning in two Middle Eastern countries (Saudi Arabia and Iraq), as well as identifying the constructs that can help enhance learners' motivation. A conceptual framework was proposed based on a modified UTAUT2, wherein trust was integrated, and new relationships were assumed among the proposed Model variables. Data were gathered using an online questionnaire from 469 higher education students of Computer Science. The collected data were analyzed with partial least squares (PLS) structural equation modeling and multi-group analysis (MGA) techniques. The results suggest significant differences in learners' perceptions from both countries. It was found that although some variables were significant in one country, they were not in the other and vice versa. Overall, the proposed framework explained 56.1% and 40.7%, respectively of the variance of behavioral intention and hedonic motivation among the Saudi sample (N = 246), and 51.1% and 41.9%, respectively of the variance of behavioral intention and hedonic motivation in the Iraqi sample (N = 223). These research outcomes are significant for educational institutions as they could help policy-makers better understand the issues facing mobile learning acceptance in terms of cultural similarities and differences. Accordingly, new strategies could be formulated to ensure improved mobile learning uptake.     

老年人在线学习平台使用意愿及设计策略研究

目的 针对人口老龄化问题,从老年人在线学习平台使用意愿及其影响因素入手,结合现有学习平台的特征,探求老年人在线学习平台的设计策略,进而增强老年人的使用意愿,使在线教育的价值得以体现。方法 首先,以文献研究为基础,结合扩展技术接受模型与创新扩散理论构建使用意愿影响因素假设模型;其次,选取研究对象进行问卷调研,并对数据进行信效度分析;最后,运用结构方程模型分析老年人在线学习平台使用意愿的主要因素和内在因果关系。结果 感知有用性与兼容性直接影响用户的使用意愿;感知易用性、感知自主性、内容质量则间接影响用户的使用意愿。结论 根据各因素导向,提出增强老年人在线学习平台用户体验设计策略,包含有效性原则、简易性原则、胜任性原则、一致性原则,以期为在线学习平台的适老化设计与改造提供有效依据。     

质量屋中顾客需求向技术特征映射的一种方法

在利用质量功能配置(QualityFunctionDeployment,QFD)进行产品规划决策时,根据顾客需求选取技术特征,是实现产品规划中顾客域到技术特征域转换进而进行产品规划的关键。建立了资源约束下最大化顾客满意程度和最大化技术特征集表现度的整数规划模型,实现了顾客需求域到技术特征域的映射,从而确定出质量屋决策中需重点考虑的技术特征项,并给出了实例。     

Study of the alloying additives and alkaline zincate solution effects on the commercial aluminum as galvanic anode for use in alkaline batteries

The corrosion behavior of different grades of commercial aluminum such as AA1040, AA5083, AA6060 and AA7075 in ZnO-containing 4 M NaOH has been determined by using open circuit potential-time measurements (OCP), galvanostatic and potentiodynamic polarization and electrochemical impedance spectroscopy (EIS). The results of scanning electron microscopy (SEM) and energy dispersive analysis of X-ray (EDAX) reveal that ZnO produces the inhibition effect by the formation of a zinc-containing deposit layer on the surface of aluminum electrodes. Although the influence of zincating on the performance of aluminum alloys and considering the amount of alloying elements such as zinc, magnesium and manganese in AA7075 and AA5083 alloys is much more than AA6060 one, the AA6060 aluminum exhibits negligible corrosion rate. Alloying aluminum with other elements and modifying the composition of the electrolyte is a necessary condition for reducing the self-corrosion of the aluminum anodes, whereas the proportion of the amount of additive elements is sufficient and important condition. As AA6060 with a low amount of Zn and Mg, but the high value of the ratio of (Mg/Zn) content (>400) can serve as a good galvanic anode in the alkaline media.     

粘胶活性碳纤维预浸剂的热分解作用及效能评选

用热失重分析方法研究了磷酸铵盐、磷酸、硫酸铵对粘胶纤维的热分解促进作用.空气的存在有利于磷酸氢二铵对粘胶的分解反应,但对其余几种的影响不大.本文提出用峰高/半高宽之比表征热分解峰的形态.该值越低,即热分解峰越平坦,表明反应越缓和,则越有利于提高粘胶纤维的碳化活化得率.实验结果证实了这一观点.磷酸氢二铵/粘胶的热分解峰最平坦,作用效果最好;磷酸二氢铵和磷酸相当,磷酸铵次之,硫酸铵作用时比表面积很低.未预浸处理的粘胶热分解最激烈,产品得率和比表面积也最低.     

A computational approach to understand the breathing dynamics and pharmaceutical aerosol transport in a realistic airways

Targeted drug delivery is an advanced method discussed in the literature for optimized treatment of diseases. However, the data for a precise understanding of pharmaceutical aerosol transport to the desired positions in the airways is not sufficient in the literature. Hence, in this work the transport and deposition of particles have been studied numerically in a realistic model of the respiratory system. The model was reconstructed based on CT-scan images of a healthy 28-year-old male and the commercial code ANSYS Fluent was used for analysis. After validation, distribution and deposition patterns of particles have been presented along with analysis of flow field dynamics. It was found that majority of particles enter the right lung while deposition is higher in the left lung and that the left lower lobe, left upper lobe and right lower lobe have the highest rate of lobar deposition. It was also observed that inertial impaction plays the dominant role in deposition of larger diameter particles at higher flow rates at the upper airways. The present findings improve our insight toward regional distribution and deposition of particles and assists in more accurate prediction of particle transport for drug delivery.     

A linear‐time method for computing the ANOS of Bernoulli and Poisson CUSUM charts

The average number of observations to signal (ANOS) is an important measure of the effectiveness of Bernoulli or Poisson cumulative sum (CUSUM) control charts. Being able to quickly and accurately calculate an ANOS vector facilitates effective control chart design. We present a linear‐time method for computing the ANOS of Bernoulli CUSUM charts and generalize to Poisson CUSUM charts. This method overcomes computation challenges associated with previously existing methods.