Search results

Advances in material agency driven by artificial intelligence (AI) have facilitated breakthroughs in material adaptivity enabling smart objects to autonomously provide individualized smart services, which makes smart objects act as social actors embedded in the real world. However, little is known about how material adaptivity fosters the infusion use of smart objects to maximize the value of smart services in customers' lives. This study examines the underlying mechanism of material adaptivity (task and social adaptivity) on AI infusion use, drawing on the theoretical lens of social embeddedness.

This study adopted partial least squares structural equation modeling (PLS-SEM), mediating tests, path comparison tests and polynomial modeling to analyze the proposed research model and hypotheses.

The results supported the proposed research model and hypotheses, except for the hypothesis of the comparative effects on infusion use. Besides, the results of mediating tests suggested the different roles of social embeddedness in the impacts of task and social adaptivity on infusion use. The post hoc analysis based on polynomial modeling provided a possible explanation for the unsupported hypothesis, suggesting the nonlinear differences in the underlying influencing mechanisms of instrumental and relational embeddedness on infusion use.

The formation mechanisms of AI infusion use based on material adaptivity and social embeddedness help to develop the business strategies that enable smart objects as social actors to exert a key role in users' daily lives, in turn realizing the social and economic value of AI.

This study advances the theoretical research on material adaptivity, updates the information system (IS) research on infusion use and identifies the bridging role of social embeddedness of smart objects as agentic social actors in the AI context.

The purpose of this study is to explore consumers’ profiles for and purchase intentions towards smart environmental objects. It segments consumers according to two apparently contradictory dimensions of smart environmental objects: environment (i.e. environmental concern and environmental beliefs) and technology (i.e. materialistic values and technological beliefs).

A cluster analysis was conducted among 658 French consumers based on their environmental concern, environmental beliefs, materialistic values, perceived usefulness and perceived ease of use. A regression analysis identifies the variables with the greatest influence on purchase intentions.

Four segments result from the analysis: unconcerned, retro eco-friendly, non-materialistic converted and converted. The converted consumer segment had the highest purchase intentions and exhibited high levels of both environmental beliefs and perceived usefulness compared with the other segments. Both environmental and technological beliefs and environmental concern influence purchase intentions more broadly.

A combined consideration of both environmental and technological beliefs is necessary to influence purchase intentions towards smart environmental objects. This study challenges some previous research that assumes a clear opposition between materialism and environmentalism.

This study proposes tailored managerial recommendations for each of the four consumer segments in the context of smart environmental objects.

This study provides novel insights into consumers’ concerns, beliefs and values in the rapidly expanding context of smart environmental objects.

A cyber world (CW) is a digitized world created on cyberspaces inside computers interconnected by networks including the Internet. Following ubiquitous computers, sensors, e‐tags, networks, information, services, etc., is a road towards a smart world (SW) created on both cyberspaces and real spaces. It is mainly characterized by ubiquitous intelligence or computational intelligence pervasion in the physical world filled with smart things. In recent years, many novel and imaginative researches have been conducted to try and experiment a variety of smart things including characteristic smart objects and specific smart spaces or environments as well as smart systems. The next research phase to emerge, we believe, is to coordinate these diverse smart objects and integrate these isolated smart spaces together into a higher level of spaces known as smart hyperspace or hyper‐environments, and eventually create the smart world. In this paper, we discuss the potential trends and related challenges toward the smart world and ubiquitous intelligence from smart things to smart spaces and then to smart hyperspaces. Likewise, we show our efforts in developing a smart hyperspace of ubiquitous care for kids, called UbicKids.

This paper aims to present a smart, sustainable supply chain practices structure on the basis of the relational view.

A method based on fuzzy cognitive map was applied to construct a relational map to introduce and implement such relational methods. Considering this relational map as a guideline, observations into particular methods and ways of applying relational methods to attain sustainable development goals across organizations has been introduced.

Primary outcomes provided a series of relational methods for the purpose of giving advice to those organizations and their suppliers for smart, sustainable supply chain. Reliance between relational methods were examined and assessed under seven meaningful groups: economic internet of things (IoT), green internet of things, social internet of things, economic supply chain, green supply chain, social supply chain and other variables.

This study guides managers toward an improved perception of the connection among IoT instances and sustainable supply to modeling smart, sustainable supply chain. Managers can determine the practices that need more focus along with the practices that are less relevant. Thus, this will help managers in the decision-making process and to organize their decisions by planning and calculating the relative importance and influence of smart, sustainable practices on each other and on the company’s smart, sustainable program.

To the best of the authors’ knowledge, this is the first approach that promptly examines and determines the interdependencies between relational methods and constructs a relational map for the purpose to introduce and analyze smart, sustainable supply chain.

This paper aims to provide a review of different types of non-wearable human identification sensors which can be applied for smart home environment.

The authors performed a systematic review to assess and compare different types of non-wearable and non-intrusive human identification sensors used in smart home environment. The literature research adds up to 5,567 records from 2000 to 2016, out of which 40 articles were screened and selected for this review.

In this review, the authors classified non-wearable human identification technologies into four main groups, namely, object-based, footstep-based, body shape-based and gait-based identification technologies. Assessing these four group of identification technologies showed that the maturity of non-wearable identification is not high and most of these technologies are verified in a lab environment. Additionally, footstep-based identification is the most popular identification approach listed in the literature.

This study contributes to the literature on human identification technologies in several ways. This paper identifies the state-of-the-art regarding non-wearable technologies which can be used in smart home environment. Moreover, the results of this paper can provide a better understanding of advantages and disadvantages of the non-wearable identification technologies.

While several warehouses are now technologically equipped and smart, the implementation of real-time analytics in warehouse operations is scarcely reported in the literature. This study aims to develop a practical system for real-time analytics of process monitoring in an internet-of-things (IoT)-enabled smart warehouse environment.

A modified system development research process was used to carry out this research. A prototype system was developed that mimicked a case company’s actual warehouse operations in Indonesia’s manufacturing companies. The proposed system relied heavily on the utilization of IoT technologies, wireless internet connection and web services to keep track of the product movement to provide real-time access to critical warehousing activities, helping make better, faster and more informed decisions.

The proposed system in the presented case company increased real-time warehousing processes visibility for stakeholders at different management levels in their most convenient ways by developing visual representation to display crucial information. The numerical or textual data were converted into graphics for ease of understanding for stakeholders, including field operators. The key elements for the feasible implementation of the proposed model in an industrial area were discussed. They are strategic-level components, IoT-enabled warehouse environments, customized middleware settings, real-time processing software and visual dashboard configuration.

While this study shows a prototype-based implementation of actual warehouse operations in one of Indonesia’s manufacturing companies, the architectural requirements are applicable and extensible by other companies. In this sense, the research offers significant economic advantages by using customized middleware to avoid unnecessary waste brought by the off-the-shelves generic middleware, which is not entirely suitable for system development.

This research’s finding contributes to filling the gap in the limited body of knowledge of real-time analytics implementation in warehousing operations. This should encourage other researchers to enhance and develop the devised elements to enrich smart warehousing’s theoretical knowledge. Besides, the successful proof-of-concept implementation reported in this research would allow other companies to gain valuable insights and experiences.

This paper theorizes ubiquitous computing as a novel configuration of the archive. Such a configuration is characterized by shifts in agency underlying archival mechanics and a pronounced rhythmic diminution of such mechanics in which the user's experiential present tense is rendered fundamentally historical. In doing so, this paper troubles the relationship between: archival mechanics such as appraisal, accession and access; the archive as a site of historical knowledge production and the pervasiveness of data-driven daily life.

By employing conceptual analysis, I analyze a classic vision of ubiquitous computing to describe the historicization of the present tense in an increasingly computerized world. The conceptual analysis employed here draws on an interdisciplinary set of literature from library and information science, philosophy and computing fields such as human-computer interaction (HCI) and ubiquitous computing.

I present the concept of the data perfect tense, which is derived from the future perfect tense: the “will have had” construction. It refers to a historicized, data-driven and fundamentally archival present tense characterizing the user's lived world in which the goal of action is to have had created data for future unspecified use. The data perfect reifies ubiquitous computing as an archive, or a site of historical knowledge production predicated on sets of potential statements derived from data generated, appraised, acquisitioned and made accessible through and by means of pervasive “smart” objects.

This paper provides foundational consideration of ubiquitous computing as a configuration of the archive through the analysis of its temporalities: a rhythmic diminution that renders users' experiential present tenses as fundamentally historical, constructed through the agency of smart devices. In doing so, it: contributes to ongoing work within HCI seeking to understand the relationship between HCI and history; introduces concepts relevant to the analysis of novel technological ecologies in terms of archival theory; and constitutes preliminary interdisciplinary steps towards highlighting the relevance of theories of the archive and archival mechanics for critiquing sociotechnical concerns such as surveillance capitalism.

Smart grid is an integration between traditional electricity grid and communication systems and networks. Providing reliable services and functions is a critical challenge for the success and diffusion of smart grids that needs to be addressed. The purpose of this study is to determine the critical criteria that affect smart grid reliability from the perspective of users and investigate the role big data plays in smart grid reliability.

This study presents a model to investigate and identify criteria that influence smart grid reliability from the perspective of users. The model consists of 12 sub-criteria covering big data management, communication system and system characteristics aspects. Multi-criteria decision-making approach is applied to analyze data and prioritize the criteria using the fuzzy analytic hierarchy process based on the triangular fuzzy numbers. Data was collected from 16 experts in the fields of smart grid and Internet of things.

The results show that the “Big Data Management” criterion has a significant impact on smart grid reliability followed by the “System Characteristics” criterion. The “Data Analytics” and the “Data Visualization” were ranked as the most influential sub-criteria on smart grid reliability. Moreover, sensitivity analysis has been applied to investigate the stability and robustness of results. The findings of this paper provide useful implications for academicians, engineers, policymakers and many other smart grid stakeholders.

The users are not expected to actively participate in smart grid and its services without understanding their perceptions on smart grid reliability. Very few works have studied smart grid reliability from the perspective of users. This study attempts to fill this considerable gap in literature by proposing a fuzzy model to prioritize smart grid reliability criteria.

The Internet of Things (IoT), as one of the new digital technologies, has created wide applications in various industries, and one of the most influential industries of this technology is the transportation industry. By integrating the IoT with the transportation industry, there will be dramatic changes in the industry, and it will provide many entrepreneurial opportunities for entrepreneurs to develop new businesses. Opportunity identification is at the heart of the entrepreneurial process, and entrepreneurs identify innovative goods or services to enter a new market by identifying, evaluating, and exploiting opportunities. Despite the desire of transportation managers to invest in the IoT and the increase in research in this area, limited research has focused on IoT-based entrepreneurial opportunities in the transportation industry. Therefore, the present study aims to identify IoT-based entrepreneurial opportunities in the transportation industry and examine their importance.

To achieve the research objective, the authors applied a mixed approach. First, adapting the lens of the industry value chain theory, a comprehensive literature review, besides a qualitative approach including semi-structured interviews with experts and thematic analysis, was conducted to identify the entrepreneurial opportunities. The identified opportunities were confirmed in the second stage using a quantitative survey method, including the Student t-test and factor analysis. Finally, the identified opportunities were weighted and ranked using the best worst method (BWM).

Entrepreneurial opportunities are classified into five main categories, including “smart vehicles”, “business partners/smart transportation supply side”, “supporting services”, “infrastructures”, and “smart transport management and control”. The infrastructures group of opportunities ranked the highest amongst the identified groups.

This study adds to the digital entrepreneurship opportunity recognition literature by addressing opportunities in a smart industry propelled by digital technologies, including developing new products or new applications of the available technologies. Additionally, inspired by the industry value chain theory, this article develops a framework including various digital entrepreneurial opportunity networks which are necessary to add value to any industry and, thus, could be applied by entrepreneurs to recognize opportunities for new intermediaries to enter other digital-based industries. Finally, the present study identifies the IoT-based entrepreneurial opportunities in the smart transportation industry and prioritizes them, providing practical insights regarding the creation of entrepreneurial ecosystems in the field of smart transportation for entrepreneurs and policymakers.

Artificially intelligent (AI) assistant-enabled smart speaker not only can provide assistance by navigating the massive amount of product and brand information on the internet but also can facilitate two-way conversations with individuals, thus resembling a human interaction. Although smart speakers have substantial implications for practitioners, the knowledge of the underlying psychological factors that drive continuance usage remains limited. Drawing on social response theory and the technology acceptance model, this study aims to elucidate the adoption process of smart speakers.

A field survey of 391 smart speaker users were obtained. Partial least squares structural equation modeling was used to analyze the data.

Media richness (social cues) and parasocial interactions (social role) are key determinants affecting the establishment of trust, perceived usefulness and perceived ease of use, which, in turn, affect attitude, continuance usage intentions and online purchase intentions through AI assistants.

AI assistant-enabled smart speakers are revolutionizing how people interact with smart products. Studies of smart speakers have mainly focused on functional or technical perspectives. This study is the first to propose a comprehensive model from both functional and social perspectives of continuance usage intention of the smart speaker and online purchase intentions through AI assistants.