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This study aims to develop a comprehensive adoption model that combines constructs from various theories and tests these theories against each other. The study combines a technology acceptance model, innovation diffusion theory and risk theory. It develops this model in a smart home applications context.

The study is based on an online survey consisting of 409 participants, and the data are analyzed using structural equation modeling.

Each theory provides unique insights into technology acceptance and numerous constructs are interrelated. Predictors from innovation diffusion and risk theory often display indirect effects through technology acceptance variables. The study identifies risk perception as a major inhibitor of use intention, mediated through perceived usefulness. Results reveal that the most important determinants of use intention are compatibility and usefulness of the application.

Studies which do not examine different theories together may not be able to detect the indirect effects of some predictors and could falsely conclude that these predictors do no matter. The findings emphasize the crucial role of compatibility, perceived usefulness and various risk facets associated with smart homes.

This study broadens the understanding about the necessity of combining acceptance and adoption drivers from several theories to better understand the usage of complex technological systems such as smart home applications.

Coronavirus Disease 2019 (COVID-19) necessitated the need for “Hospital-at-home” improvisations that involve wearable technology to classify patients within households before visiting health institutions. Do-It-Yourself wearable devices allow for the collection of health data leading to the detection and/or prediction of the prevalence of the disease. The sensitive nature of health data requires safeguards to ensure patients’ privacy is not violated. The previous work utilized Hyperledger Fabric to verify transmitted data within Smart Homes, allowing for the possible implementation of legal restrictions through smart contracts in the future. This study aims to explore privacy-enhancing authentication schemes that are operated by multiple credential issuers and capable of integration into the Hyperledger ecosystem.

Design Science Research is the methodology that was used in this study. An architecture for ABC-privacy was developed and evaluated.

While the privacy-by-design architecture enhances data privacy through edge and fog computing architecture, there is a need to provide an additional privacy layer that limits the amount of data that patients disclose. Selective disclosure of credentials limits the number of information patients or devices divulge.

The evaluation of this study identified Coconut as the most suitable attribute-based credentials scheme for the Smart Homes Patients and Health Wearables use case Coconut user-centric architecture Hyperledger integration multi-party threshold authorities public and private attributes re-randomization and unlinkable revelation of selective attribute revelations.

Digital voice assistants use wake word engines (WWEs) to monitor surrounding audio for detection of the voice assistant's name. There are two failed conditions for a WWE, false negative and false positive. Wake word false positives threaten a loss of personal privacy because, upon activation, the digital assistant records audio to the voice cloud service for processing.

This observational study attempted to identify which Amazon Alexa wake word and Amazon Echo smart speaker resulted in the fewest number of human voice false positives. During an eight-week period, false-positive data were collected from four different Amazon Echo smart speakers located in a small apartment with three female roommates.

Results from this study suggest the number of human voice false positives are related to wake word selection and Amazon Echo hardware. Results from this observational study determined that the wake word Alexa resulted in the fewest number of false positives.

This study suggests Amazon Alexa users can better protect their privacy by selecting Alexa as their wake word and selecting smart speakers with the highest number of microphones in the far-field array with 360-degree geometry.

Failed deliveries (i.e. deliveries not accomplished due to the absence of customers) represent a critical issue in B2C (Business-to-consumer) e-commerce last-mile deliveries, implying high costs for e-commerce players and negatively affecting customer satisfaction. A promising option to reduce them would be scheduling deliveries based on the probability to find customers at home. This work proposes a solution based on presence data (gathered through Internet of Things [IoT] devices) to organise the delivery tours, which aims to both minimise the travelled distance and maximise the probability to find customers at home.

The adopted methodology is a multi-method approach, based on interviews with practitioners. A model is developed and applied to Milan (Italy) to compare the performance of the proposed innovative solution with traditional home deliveries (both in terms of cost and delivery success rate).

The proposed solution implies a significant reduction of missed deliveries if compared to the traditional operating mode. Accordingly, even if allocating the customers to time windows based on their availability profiles (APs) entails an increase in the total travel time, the average delivery cost per parcel decreases.

On the academic side, this work proposes and evaluates an innovative last-mile delivery (LMD) solution that exploits new AI (Artificial Intelligence)-based technological trends. On the managerial side, it proposes an efficient and effective novel option for scheduling last-mile deliveries based on the use of smart home devices, which has a significant impact in reducing costs and increasing the service level.

Consumers' perceptions of product intelligence affect their willingness to accept smart offerings. This paper explores how people perceive various smart products based on their smartness profiles, composed of five distinct smartness facets. Additionally, the study investigates how these perceptions of product intelligence impact consumers' evaluation of factors that either promote or impede the adoption of smart products. These factors are examined as potential mediators in the adoption process. This paper aims to determine if the value-based adoption model can be applied to a broad range of smart service systems.

Consumers assessed one of 28 smart products in a scenario-based quantitative study. Multilevel structural equation modeling (SEM) is used to test the conceptual model, taking the nested data structure into account.

The findings show that product smartness essentially enhances usage intention via adoption drivers (enjoyment and usefulness) and reduces usage intention via adoption barriers (intrusiveness). In particular, the ability to interact in a humanlike manner increases the benefits consumers perceive, which in turn increases consumer acceptance. Only the smartness characteristic of awareness impairs usage intention, mediated by the perceived benefits of enjoyment and usefulness.

In contrast to previous research, which usually focuses on single smart products, this work examines a variety of different products, which allows for better transferability of the results to other smart offerings. Furthermore, prior research has mainly focused on single facets of product smartness or researched smartness on an aggregated level. By considering the consumer perception of each smartness facet, the authors gain deeper insights into the perceptual differences regarding product smartness and how this affects technology adoption via conflicting key acceptance drivers and barriers.

This article’s purpose is to develop The Model for Smart, Self-learning and Adaptive Resilience Building (SARB).

Products and patents of methods and systems analysis was carried out in the fields of BIM application, Smart, Self-learning and Adaptive Resilience Building. Based on other researchers’ findings, The SARB Model was proposed.

Analysis of the literature showed that traditional decisions on the informational modelling do not satisfy all the needs of smart building technologies owing to their static nature. The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life.

The SARB Model was developed to take care of its efficiency from the brief stage to the end of its service life. The SARB Model does have some limitations: (1) the processes followed require the collection of much unstructured and semi-structured data from many sources, along with their analyses to support stakeholders in decision-making; (2) stakeholders need to be aware of the broader context of decision-making and (3) the proposal is process-oriented, which can be a disadvantage during the model’s implementation.

Two directions can be identified for the practical implications of the SARB Model. The initial expectation is the widespread installation of SARB Model within real estate and construction organisations. Furthermore, development of the SARB Model will be used to implement the ERASMUS+ project, “Advancing Skill Creation to ENhance Transformation—ASCENT” Project No. 561712-EPP-1-2015-UK-EPPKA2-CBHE-JP.

The practical implications of this paper are valuable.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.

The authors seek to understand the process of digital servitization as a shift of manufacturing companies from the provision of standard products and services to smart solutions. Specifically, the authors focus on changes in the business model (i.e. the value proposition, the value delivery system and the value capture mechanism) for digital servitization.

The authors examine a Chinese air conditioner manufacturer, Gree, who became the global leader with their smart solutions. These solutions included performance-based contracts underpinned by artificial intelligence (AI)-powered air conditioners that automatically adjust to environmental changes and are capable of remote monitoring and servicing thanks to its Internet of things (IoT) technology.

To successfully offer smart solution value propositions, a manufacturer needs an ecosystem value delivery system composed of suppliers, distributors, partners and customers. Once the ecosystem relationships are well aligned, the manufacturer gains value with multiple value capture mechanisms (i.e. efficiency, accountability, shared customer value and novelty). To arrive at this point, a manufacturer has to pass through different stages that are characterized by both discontinuous and continuous interplay between business models and digital technologies. At the beginning of each stage, new value propositions and value delivery systems are first discontinuously created and then enabled with digital technology. As a result, new value capture mechanisms are activated. Meanwhile, the elements of the existing business model are continuously improved.

By combining process-perspective and business-model lenses, the authors offer nuanced insights into how digital servitization unfolds.

Executives can obtain insights into the business model elements, they need to change over the course of digital servitization and how to manage the process.

A longitudinal case study of a traditional manufacturer that has achieved stellar success through digital servitization business models development.

This study aims to provide a systematic review about the Internet of Things (IoT) and its impacts on happiness. It intends to serve as a platform for further research as it is sparse in in-depth analysis.

This systematic review initially observed 2,501 literary articles through the ScienceDirect and WorldCat search engines before narrowing it down to 72 articles based on subject matter relevance in the abstract and keywords. Accounting for duplicates between search engines, the count was reduced to 66 articles. To finally narrow down all the literature used in this systematic review, 66 articles were given a critical readthrough. The count was finally reduced to 53 total articles used in this systematic review.

This paper necessitates the claim that IoT will likely impact many aspects of our everyday lives. Through the literature observed, it was found that IoT will have some significant and positive impacts on people's welfare and lives. The unprecedented nature of IoTs impacts on society should warrant further research moving forward.

While the literature presented in this systematic review shows that IoT can positively impact the perceived or explicit happiness of people, the amount of literature found to supplement this argument is still on the lower end. They also necessitate the need for both greater depth and variety in this field of research.

Since technology is already a pervasive element of most people’s contemporary lives, it stands to reason that the most important factors to consider will be in how we might benefit from IoT or, more notably, how IoT can enhance our levels of happiness. A significant implication is its ability to reduce the gap in happiness levels between urban and rural areas.

Currently, the literature directly tackling the quantification of IoTs perceived influence on happiness has yet to be truly discussed broadly. This systematic review serves as a starting point for further discussion in the subject matter. In addition, this paper may lead to a better understanding of the IoT technology and how we can best advance and adapt it to the benefits of the society.

Internet of Things’ (IoT’s) first wave started with tracking services for better inventory management mainly using radio frequency identification (RFID) technology. Later on, monitoring services became one of the major interests, including sensing technologies, and then more actuation for remote control-type of IoT applications such as smart homes, smart cities and Industry 4.0. In this paper, the authors focus on the RFID technology impairment. They propose to take advantage of the mature IoT technologies that offer native service discovery such as blutooth or LTE D2D ProSe or Wifi Direct. Using the automatic service discovery in the new framework will make heterogeneous readers aware of the presence of other readers and this will be used by the proposed distributed algorithm to better control the multiple RFID reader interference problem. The author clearly considers emerging Industry 4.0 use case, where RFID technology is of major interest for both identification and tracking. To enhance the RFID tag reading performance, collisions in the RFID frequency should be minimized with reader-to-reader coordination protocols. In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation.

In this paper, the author proposes a simple distributed reader anti-collision protocol named DiSim that makes use of proximity services of IoT network and is compliant with the current RFID standards. The author evaluates the efficiency of the proposal via simulation to study its behavior in very dense and heterogeneous RFID environments. Specifically, the author explores the coexistence of powerful static readers and small mobile readers, comparing the proposal with a standard ETSI CSMA method. The proposal reduces significantly the number of access attempts, which are resource-expensive for the readers. The results show that the objectives of DiSim are met, producing low reader collision probability and, however, having lower average readings per reader per time.

DiSim is evaluated with the ETSI standard LBT protocol for multi-reader environments in several environments with varied levels of reader and tag densities, having both static powerful RFID readers and heterogeneous randomly moving mobile RFID readers. It effectively reduces the number of backoffs or contentions for the RFID channel. This has high reading success rate due to the avoided collisions; however, the readers are put to wait, and DiSim has less average readings per reader per time. As an additional side evaluation, the ETSI standard LBT mechanism was found to present a good performance for low-density mid-coverage scenarios, however, with high variability on the evaluation results.

To show more results, the author needs to do real experimentation in a warehouse, such as Amazon warehouse, where he expects to have more and more robots, start shelves, automatic item finding on the shelve, etc.

Future work considers experimentation in a real warehouse equipped with heterogeneous RFID readers and real-time analysis of RFID reading efficiency also combined with indoor localization and navigation for warehouse mobile robots.

More automatization is expected in the future; this work makes the use of RFID technology more efficient and opens more possibilities for services deployment in different domains such as the industry which was considered not only in this paper but also in smart cites and smart homes.

Compared to the literature, the proposal offers the advantage to not be dependent on a centralized server controlling the RFID readers. It also offers the possibility for an existing RFID architecture to add new readers from a different manufacturer, as the readers using the approach will have the possibility to discover the capabilities of the new interaction other RFID readers. This solution takes advantage of the available proximity service that will be more and more offered by the IoT technologies.