Artificial Intelligence (AI) is transforming the way retail stores operate. AI-Powered Automated Retail Stores are the next revolution in physical retail. Consumers are facing fully automated technology in these retail stores. Therefore, it is necessary to scrutinize the antecedents of consumers’ intention to shop at AI-Powered Automated Retail Stores. This study delves into this area to find the predictors of consumers’ intention to shop at AI-Powered Automated Retail Stores. It extends the technology readiness and acceptance model by the addition of AI contextspecific constructs such as Perceived Enjoyment, Customization and Interactivity from the present literature. The proposed model is tested by surveying 1250 consumers & the data is analyzed using the PLS-SEM technique and empirically validated. The outcome of the study reveals that Innovativeness and Optimism of consumers affect the perceived ease and perceived usefulness. Insecurity negatively affects the perceived usefulness of AI-powered automated retail stores. Perceived ease of use, perceived usefulness, perceived enjoyment, customization and interactivity are significant predictors of shopping intention of consumers in AI-powered automated stores. This research presents insightful academic and managerial implications in the domain of retailing and technology in retail.
Keywords: TRAM | PLS-SEM | Perceived enjoyment | Customization | Interactivity | Artificial intelligence-powered automated | retail stores

Information Systems (IS) and the platforms they provide can be conceived of as a stimulus which engenders customers’ reactions. In this respect, banks could benefit from a keen understanding of consumers’ individual needs in the context of their personality traits in their efforts to optimize the use of IS for service development and management. In accordance with this, the present study adopted the Trait Hierarchical Model (THM) and the Optimum Stimulation Level Theory (OSLT), to explore (1) the influence of Optimum Stimulation Level (OSL), a broad personality trait that determines individuals’ need for stimulation on Mobile Banking Discontinuous Usage Intentions (MBDUI), (2) the mediating effects of stable IT-specific traits – Microcomputer Playfulness (MCP) and Personal Innovativeness in Information System (PIIT) on the OSL – MBDUI relations and (3) the interaction of Perceived Ease of Use (PEOU) on the direct and indirect OSL – MBDUI relation. The findings supported most of the hypothesized paths, buttressing the theoretical underpinnings of the THM as well as the OSLT, and empirically extending the OSL framework. The study further outlines practical measures for mbanking service management and directions for future studies
Keywords: M-Banking | Mobile Banking Discontinuous Usage Intention | Optimum Stimulation Level | IT-specific Traits

According to the United Nations Sustainable Development Goal No. 3 (SDG – Goal 3), for sustainable devel opment it is imperative to ensure health and well-being across all ages, and is achievable only through effective and continuous healthcare monitoring. But in India and other third world countries, healthcare monitoring is poor compared to other countries in the world, in spite of it being affordable. The global healthcare smart wearable healthcare (SWH) devices market is expected to rise up at a CAGR (Compound Annual Growth Rate) of 5.6% and by 2020 it is expected to reach 25 Billion (GVR Report, 2016). The growing incidences of lifestyle diseases, sedentary lifestyle, busy work schedules, technological advancements in healthcare monitoring devices, and increased usage of remote devicesseems to be some of the important factors fuelling this growth. Some of the major players in this segment are Abbott Laboratories, Philips Healthcare, Life Watch, GE Healthcare, Omron Healthcare, Siemens Healthcare and Honeywell International Inc. etc. But in spite of the healthcare monitoring devices are being predicted to be technologically innovative and providing advanced as well as basic health care monitoring features and available in various price ranges based on the features, we wanted to empirically study the attitude towards adoption of such devices in India. India has traditionally been having a very lackadaisical attitude towards healthcare monitoring. In such a context, what would be the factors influencing the adoption of SWH devices. Remote health monitoring can enhance the nature of wellbeing administration and to lessen the aggregate expense in human services by maintaining a strategic distance from pointless hospitalizations and guaranteeing that the individuals who need critical consideration get it sooner. This empirical investigation would provide a detailed insight as to how these wearable Internet Of Things devices would bring about a revolution in the healthcare industry. It would also provide the future prospect of IOT devices in this sector and how the probability of increase in its usage can be increased with time. The paper explores intrusiveness (INTR), Comfort (C), perceived usefulness (PU) and perceived ease of use (EOU) of SWH devices. The study hypothesized the Impact of PU and EOU, INTR and C on attitude and intention to use towards adoption of SWH devices. Partial Least Square Structured Equation Modeling (PLS – SEM) methodology was applied to explore the relationships between the concepts and hypothesis. The data was collected from 273 respondents. The age group of the respondents was between 25 and 40 years. The results indicated that intrusiveness and comfort do not have a significant direct impact on Intention to use BI (Behavior Intention) BI SWH devices. At the same time Intrusiveness had a significant impact on PU of SWH devices and Comfort has a strong significant impact on PU and EOU of smart wearables. The research has strong implications in the current emerging context of smart wearables, their design and effectiveness. Also the research can have lasting implications on elderly health and well-being. There are very few empirical studies in the area of SWH devices. Most of the studies till now are conceptual studies or providing technology architectures and frameworks. The research in this area is still at a very nascent stage and very few studies have been done to explore the use and adoption of SWH devices.
Keywords: Internet of things ، Smart healthcare ، Smart cities ، RFID ، Healthcare computing ، Healthcare systems ، Innovation management

The scale and complexity of big data quickly exceed the reach of direct human comprehension and increasingly require machine assistance to semantically analyze, organize, and interpret vast and diverse sources of big data in order to unlock its strategic value. Due to its volume, velocity, variety, and veracity, big data integration challenges overwhelm traditional integration approaches leaving many integration possibilities out of reach. Unlocking the value of big data requires innovative technology. Organizations must have the innovativeness and data capability to adopt the technology and harness its potential value. The Semantic Web (SW) technology has demonstrated its potential for integrating big data and has become important technology for tackling big data. Despite its importance to manage big data, little research has examined the determinants affecting SW adoption. Drawing upon the technology–organization–environment framework as a theory base, this study develops a research model explaining the factors affecting the adoption of SW technology from IT professionals’ perspective, specifically in the context of corporate computing enterprises. We validate the proposed model using a set of empirical data collected from IT professionals including IT managers, system architects, software developers, and web developers. The findings suggest that perceived usefulness, perceived ease of use, organization’s innovativeness, organization’s data capability, and applicability to data management are important drivers of SW adoption. This study provides new insights on theories of organizational IT adoption from IT professionals’ perspectives tailored to the context of SW technology.
Keywords: Semantic Web, IT professionals perspective Technology Adoption, Technology Organization-Environment Framework, Innovation Diffusion Theory