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The purpose of this paper is to investigate the implications for supply chain risk management (SCRM) by applying internet of things (IoT). Therefore, the impact and effects on the SCRM process, as well as the internal and external pathway and the outcome of SCRM are examined.

This study adopts a multiple case study methodology with twelve companies from the manufacturing industry. This study is guided by the information processing theory (IPT) and a theory-grounded research framework to provide insights into information requirements and information processing capabilities for IoT-supported SCRM.

The studied cases demonstrate an increase in data availability in the companies that contribute to improved process transparency and process management. Furthermore, the process steps, risk transparency, risk knowledge and risk strategies have been enhanced, which enabled improved SCRM performance by fitting information requirements and information processing capabilities, thus allowing for competitive advantage.

This study offers in-depth insights for SCRM managers into the structure of IoT systems, primary use cases and changes for the process itself. Furthermore, implications for employees, incentives and barriers are identified, which could be used to redesign SCRM.

This study addresses the requirement for additional empirical research on technology-enhanced SCRM, supported by IPT as a theoretical foundation. The radical change of SCRM by IoT is demonstrated while discussing the human role, implications for SCRM strategies and identifying relevant topics for future development.

Internet of Things (IoT) interconnects many heterogeneous devices to each other, collecting and processing large volumes of data for decision making without human intervention. However, the information security concern it brings has attracted quite a lot of attention, and, at this stage, the smart step would be to analyze the security issues of IoT platform and get to the state of readiness before embarking upon this attractive technology. The purpose of this paper is to address these issues.

IoT risk assessment through the application of the analytical hierarchy process (AHP), a favorite multi-criteria decision making technique, is proposed. The IoT risks are prioritized and ranked at different layers, before which a well-defined IoT risk taxonomy is defined comprising of 25 risks across six layers of the IoT model for developing control and mitigation plans for information security of IoT.

People and processes layer, network layer and applications layer are the top three critical layers with risks like the lack of awareness, malware injection, malicious code injection, denial of service and inefficient policies for IoT practice get the highest priority and rank. Pareto analysis of the overall risk factors revealed that the top ten factors contribute to 80 percent of the risks perceived by information security experts.

The study focuses only on certain predefined constructs or layers of the IoT model traced from legacy studies. It is essential to re-look these constructs on a timely basis to prolong the results’ validity. The study’s empirical scope is confined only to the risk perception of select IoT experts and does not encompass a broader segment of the IoT ecosystem. Therefore, the risks assessment may not be sweeping to a bigger audience.

The study implications are two-fold: one it consolidates the earlier siloed works to intensify the need for risk assessment in the IoT domain, and second the study brings yet another contextual avenue of extending the application AHP and Pareto principle combination. The paper also draws specific critical organizational interventions about IoT risks. A comprehensive approach to prioritizing and ranking IoT risks are present in this research paper.

The contribution of this study to the benchmarking of IoT risk assessment is two-fold. One, a comprehensive risk assessment taxonomy is proposed, and two, the risks are prioritized and ranked to give a convincing reference for the organizations while making information security plans for IoT technology.

The purpose of this paper is to offer a comprehensive overview of challenges and risks of the Internet of Things (IoT) in supply chain management (SCM) and provide a structured framework for classifying and analyzing the relevant literature to deduce insights for research and practice.

A systematic literature review (SLR) of 102 peer-reviewed journal articles on the topic of IoT in SCM was conducted.

This review identifies, categorizes and describes the relevant literature regarding the dimensions time and specificity. The resulting framework contains a holistic overview including focus areas and relations of macro-environmental, network-related and organizational challenges and risks. Furthermore, this review represents a conceptual framework for future research, considering the multidisciplinary body of the subject and provides an analysis of the timeline of literature, journals and used methodologies.

This study offers valuable insights into IoT and its impact on applications, processes and the structure of organizations and supply chains (SCs). The identification of challenges and risks helps to prepare for changes in the future because of the disruptive nature of this technology.

The originality of this paper lies in the synthesis of the fragmented body of literature of IoT challenges and risks for SCM. The derived framework and identification of relations and research gaps provide the foundation for further research to evaluate the relations between challenges and risks and offer solutions.

The purpose of this study is to investigate the influence that technological, environmental and organizational factors have on the rate of Internet of Things (IoT) adoption within the logistics industry. In addition, the moderating effect that the risk factor has on the technological, environmental and organizational factors regarding the implementation of IoT in logistics.

For the purpose of testing the models and hypotheses, a survey was carried out in order to collect the responses from currently employed individuals at various companies working in the field of logistics or IoT. For the purpose of analysis, the authors made use of the partial least squares structure equation model (PLS-SEM) technique.

Findings of this study concluded that technology- and environmental-related factors significantly affect the adoption of IoT in logistics, while risk acts as a moderator for the technological-related factor only in the adoption of IoT in logistics.

The relevance of the authors' study lies in the growing importance of IoT in logistics and the need for logistics companies to understand the factors that impact the adoption of IoT in their operations. By identifying and analyzing the factors that influence IoT adoption in logistics, the authors' study provides valuable insights that can help logistics companies make informed decisions about whether and how to adopt IoT.

The research will help organizations make strategies for the successful adoption of IoT and ease the lives of all the stakeholders.

In this research, the authors attempted to find the factors that influence the adoption of IoT in logistics management. The influence of the technological, environmental, organizational and risk-related factors on the adoption of IoT in logistics management was studied. The moderating effect of risk over these factors on the adoption of IoT in logistics was also analyzed. This is original work and has never been done earlier.

This study aims to analyze and synthesize literature on consumer privacy-related behavior and intelligent device-to-device interactions within the Internet of Things (IoT).

We conducted a systematic review using Elsevier’s Scopus database, focusing on studies published in English from 2000 to 2023. The review targeted articles within selected social sciences and business disciplines, specifically concerning consumer behavior in IoT contexts.

We categorized the privacy literature into three thematic clusters: legislation and policy, business implications and consumer behavior. Within the consumer behavior cluster, our analysis indicates a shift from general Internet and e-commerce privacy concerns prior to 2016, toward issues related to advertising and policy between 2017 and 2018, and increasingly toward pronounced concerns in technological systems, particularly IoT, from 2019 onwards. We identify eight distinct areas of privacy concern within IoT and propose a framework that links antecedents and privacy concerns to subsequent attitudes and behaviors. This framework highlights varying patterns of information disclosure and bridges theoretical constructs with empirical research in IoT privacy.

Originality lies in enhancing the Antecedents-Privacy Concerns-Outcomes (APCO) macro-model by integrating diverse theoretical perspectives on technological and individual-specific antecedents, alongside privacy concerns and beliefs. This comprehensive integration enriches the framework, enabling it to predict and categorize consumer behavior in IoT environments more effectively. The revised model provides a robust tool for understanding privacy-related behavior within the IoT, significantly enriching its theoretical relevance and practical applicability.

Since the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage specific supply chain risks, i.e. maintaining good environmental conditions, and ensuring occupational safety in the cold environment. The purpose of this paper is to propose an Internet of Things (IoT)-based risk monitoring system (IoTRMS) for controlling product quality and occupational safety risks in cold chains. Real-time product monitoring and risk assessment in personal occupational safety can be then effectively established throughout the entire cold chain.

In the design of IoTRMS, there are three major components for risk monitoring in cold chains, namely: wireless sensor network; cloud database services; and fuzzy logic approach. The wireless sensor network is deployed to collect ambient environmental conditions automatically, and the collected information is then managed and applied to a product quality degradation model in the cloud database. The fuzzy logic approach is applied in evaluating the cold-associated occupational safety risk of the different cold chain parties considering specific personal health status. To examine the performance of the proposed system, a cold chain service provider is selected for conducting a comparative analysis before and after applying the IoTRMS.

The real-time environmental monitoring ensures that the products handled within the desired conditions, namely temperature, humidity and lighting intensity so that any violation of the handling requirements is visible among all cold chain parties. In addition, for cold warehouses and rooms in different cold chain facilities, the personal occupational safety risk assessment is established by considering the surrounding environment and the operators’ personal health status. The frequency of occupational safety risks occurring, including cold-related accidents and injuries, can be greatly reduced. In addition, worker satisfaction and operational efficiency are improved. Therefore, it provides a solid foundation for assessing and identifying product quality and occupational safety risks in cold chain activities.

The cold chain is developed for managing environmentally sensitive products in the right conditions. Most studies found that the risks in cold chain are related to the fluctuation of environmental conditions, resulting in poor product quality and negative influences on consumer health. In addition, there is a lack of occupational safety risk consideration for those who work in cold environments. Therefore, this paper proposes IoTRMS to contribute the area of risk monitoring by means of the IoT application and artificial intelligence techniques. The risk assessment and identification can be effectively established, resulting in secure product quality and appropriate occupational safety management.

This study aims to determine how Internet of Things (IoT) risks and benefits affect both the intention to use and actual use of a smartwatch.

The stimulus–organism–behavior–consequence (SOBC) hypothesis is used to explain the mechanisms underpinning the discontinuity between intention and technology usage. A total of 394 questionnaires distributed to smartwatch users were analyzed, using convergent analysis, discriminant analysis and structural modeling.

The IoT’s technical features, such as continuous connectivity and real-time value, serve as effective stimuli for smartwatches, positively influencing individuals’ responses and behavioral consequences associated with smartwatch usage. While IoT risks such as data, performance and financial have no negative relationship with the usefulness of smartwatches, data and financial risks have a negative influence on their ease of use. Additionally, as ease of use and usefulness have a positive impact on intention to use, users’ behavior is positively influenced by their intentions to use a smartwatch.

The study applies technology acceptance theory and the SOBC paradigm to smartwatches to determine if users’ intentions to use them impact their behavior. Furthermore, the research analyzed the technical elements of smartwatches in terms of IoT advantages and risks.

El objetivo del presente estudio es determinar cómo los riesgos y beneficios del Internet de las Cosas afectan tanto a la intención de uso como al uso real de un smartwatch.

Se utiliza el modelo Estímulo-Organismo-Comportamiento-Consecuencia (SOBC) para explicar los mecanismos que sustentan la discontinuidad entre la intención y el uso de la tecnología. Se analizaron 394 cuestionarios distribuidos a usuarios de smartwatches, empleando análisis convergente, análisis discriminante y modelización estructural.

Las características técnicas del IoT, como la conectividad continua y el valor en tiempo real, sirven como estímulos efectivos para los smartwatches, influyendo positivamente en las respuestas de los individuos y en las consecuencias conductuales asociadas al uso del smartwatch. Mientras que los riesgos de la IO, como los datos, el rendimiento y los financieros, no tienen una relación negativa con la utilidad de los smartwatches, los riesgos de los datos y los financieros influyen negativamente en su facilidad de uso. Además, dado que la facilidad de uso y la utilidad tienen un impacto positivo en la intención de uso, el comportamiento de los usuarios está positivamente influenciado por sus intenciones de usar un smartwatch.

El estudio aplica la teoría de la aceptación de la tecnología y el paradigma SOBC a los smartwatches para determinar si las intenciones de uso de los usuarios influyen en su comportamiento. Además, la investigación analiza los elementos técnicos de los smartwatches en cuanto a las ventajas y los riesgos del IoT.

本研究的目的是确定物联网的风险和利益如何影响智能手表的使用意向和实际使用。

刺激-组织-行为-后果（SOBC）假说被用来解释意图和技术使用之间不连续的基础机制。对发放给智能手表用户的394份调查问卷进行了分析, 采用了收敛分析、判别分析和结构模型法。

物联网的技术特点, 如持续连接和实时价值, 作为智能手表的有效刺激, 对个人的反应和与智能手表使用相关的行为后果产生积极影响。虽然数据、性能和财务等物联网风险与智能手表的有用性没有消极关系, 但数据和财务风险对其易用性有消极影响。此外, 由于易用性和有用性对使用意图有积极影响, 用户的行为受到他们使用智能手表的意图的积极影响。

该研究将技术接受理论和SOBC范式应用于智能手表, 以确定用户的使用意图是否影响其行为。此外, 该研究还从物联网的优势和风险方面分析了智能手表的技术要素。

This study aims to investigate the ethical issues related to the internet of Things (IoT) deployment in small- and medium-sized enterprises (SMEs) from an individual employee's perspective. To provide researchers and practitioners with concrete tools for examining these matters, an ethical framework dedicated to IoT is introduced.

First, the applicability of Mason's original privacy, accuracy, property and accessibility (PAPA) framework is studied in the IoT context. Second, issue category additions are proposed based on the identified coverage limitations of PAPA.

While the original PAPA framework can be utilised as a generic ethical evaluation tool, it lacks coverage of several IoT-specific issue areas. To thoroughly address the ethical risks associated with IoT, two additional categories are introduced.

The new framework requires further validation to ensure its applicability and to identify potential modification requirements in continuously evolving IoT ecosystems.

Considering the lack of ethical IoT frameworks, this study provides organisations with a practical framework for analysing the ethical issues in IoT deployment.

Ethical standards for IoT have not been sufficiently addressed in the current literature and frameworks, making the ethical considerations dependent on subjective stances. Thus, there is an acute demand for a practical framework that outlines the general ethical standards, helping its users to thoroughly address the potential ethical issues.

While the use of IoT keeps growing in SMEs, there is an apparent lack of ethical guidelines. This study contributes to the gap by introducing a preliminary framework for both practical use and further theoretical development.

The internet of things (IoT) is becoming an increasingly inescapable part of society. IoT paradigm cannot function without the networking infrastructure. High-speed data networks are essential to enable the IoT future. Thus, the purpose of this study is on the identification of risks that influence the development, installation and operation of information and communication technology (ICT) infrastructure network project cost outcomes. So far, there has been little attention has been paid to risks problems in these types of IoT enabling projects.

This research follows a quantitative analysis approach. Data for this study were collected by a survey from 209 professionals. Multiple regression analysis was used to model the relationship between risks and outturn cost of infrastructure needed to enable the operation of IoT technologies.

The main risk factors that were identified were planning and development, people and management, operations, technology and hardware.

This research has expanded the existing literature by documenting and clustering ICT infrastructure network project risks into themes, and has developed a scale (risk statements) for measuring such risks. Further, the research has advanced the understanding by identifying the most likely risks that will contribute to the overrun of these projects.

This research establishes a reliable regression method for the assessment of the risks that influence the development, installation and operation of ICT infrastructure network projects outturn cost. No other research has measured or studied the risks in this type of project.

The purpose of this paper is to identify the risks involved in the construction project based on a literature survey (LS), to develop a project risk management (PRM) framework based on Industry 4.0 technologies and to demonstrate the developed framework using Internet of Things (IoT) technology.

A comprehensive LS was carried out to know the different risks involved in the construction project and developed a PRM framework based on Industry 4.0 technologies to increase the effectiveness and efficiency of PRM. Heavy equipment and parameters were identified to demonstrate the developed framework based on IoT technology of Industry 4.0.

This paper demonstrates Industry 4.0 in the various stages of PRM. LS has identified 21 risks for a construction project. The demonstration of the PRM framework has identified the sudden breakdown of equipment and uncertainty of equipment as one of the critical risks associated with heavy equipment of construction project.

The project complexity and features may add a few more risks in PRM.

The PRM framework based on Industry 4.0 technologies will increase the success rate of the project. It will enhance the efficiency and effectiveness of PRM.

The developed framework is helpful for the effective PRM of construction projects. The demonstration of PRM framework using IoT technology provides a logical way to manage risk involved in heavy equipment used in a construction project.