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This paper systematically reviews the evolution of Internet of Things (IoT) research in business and management over the past decade and a half. It synthesizes current knowledge, identifies major themes, gaps, and future opportunities to guide scholars on potential research directions within this exponentially growing domain.

A structured systematic literature review methodology filtered IoT publications across business/management journals using Scopus database. Detailed thematic and bibliometric analyses chronologically mapped the progress of peer-reviewed articles from 2005–2023. Both quantitative metrics and qualitative coding inductively revealed historical trends, topics, applications and research implications.

Analysis uncovered six primary IoT research themes - business models, technology, data, customers, organizations, and sustainability. Dominant focuses were found on technological enablers, business model innovation and customer experience transformations. While technical aspects are well-documented, strategic technology integrations and organizational change management require greater emphasis.

Focus restricted to academic articles published in management journals risks missing relevant papers published in other fields. Screening process involved some subjectivity. Lacks geographic analysis of research contexts. The rapidly evolving nature of technology domain risks findings’ generalizability.

Key enablers and success factors that we identified may support managerial decision making when it comes to IoT adoption.

We discuss advancing IoT innovation through ethics and sustainability lenses and these may help ensure responsible adoption.

This analysis weaves together the extant literature and offers an evidence-based research agenda for management scholars by chronicling the state, evolution, influential factors, and future opportunities within IoT literature. It highlights major thematic shifts and priority gaps to address.

This study aims to assess the use of the Internet of Things (IoT) in retail stores to improve supply chain visibility and integration.

This study employed a qualitative methodology with data collected using semi-structured interviews from a sample selected using purposive sampling. The population consists of 48 employees, of which 6 were selected for the sample as they worked directly with IoT and supply chain issues. Participants were from a SPAR franchise store (Samenwerken Profiteren Allen Regalmatig).

Thematic analysis was used to analyse the transcribed data from the interviews. The themes identified include supply chain visibility, supply chain integration and IoT. The findings indicate that the main IoT used is an organisational-wide system, the SIGMA (SPAR Integrated Goods Management Application) system. Other technologies that aid supply chain visibility and integration are geotags, the internet, WhatsApp social media applications, emails and scanners.

From the findings, this study recommends that IoT systems should be frequently updated to reflect current trends and that IoT systems should enable the integration of small and medium Enterprises (SMEs) suppliers.

The Fourth Industrial Revolution has ushered in new technologies that revolutionise business operations. Among these technologies is the IoT, which has ushered in a new connectivity area. However, there is little research on the use of IoT for supply chain visibility and integration in the South African retail sector. It provides sector-specific insights and recommendations for retailers, which might not be covered in general supply chain management literature.

Digital supply chains require nascent technologies like blockchain and Internet of Things (IoT). There is a need to develop a roadmap for the implementation of these technologies, as they require a huge amount of resources and infrastructure. The purpose of this paper is to analyze the challenges of implementing blockchain-IoT integrated architecture in the green supply chain and develop strategies for the same.

After a thorough literature survey of Scopus-indexed journals and books, 37 barriers were identified, which were then brought down to 15 barriers after confirming with industry and academic experts using the Delphi method. Using the total interpretive structural modeling (TISM) method and cross-impact matrix multiplication applied to classification (MICMAC) analysis, the barriers were modeled, and finally, strategies were formulated using a concept map to handle the barriers in the blockchain-IoT integrated architecture for a green supply chain.

This paper presents the research on barriers that can be considered for incorporating blockchain and IoT in the green supply chain. It was found from the TISM model that environmental concerns are Level-1 barriers and need to be addressed by developing appropriate technology and allocating funds for the same. An integrated ecosystem with blockchain and IoT is developed.

The focus of this study was on the challenges of blockchain and IoT; hence, it is required to extend the research and find challenges for different industries and also analyze the criteria using other multi-criteria decision-making (MCDM) methods. Further research is required for the integration of blockchain-IoT with supply chain functions.

The transformation of a traditional supply chain into a green supply chain is possible with the integration of technologies. This research work and the strategies developed are useful to managers and practitioners working on technology implementation. Planning resources and addressing key barriers is possible with the concept maps and architecture developed.

Green supply chain management (SCM) is gaining importance in industry as well as the academic sector due to government Policies and norms worldwide for reducing emissions and encouraging environment-friendly production systems. Incorporating blockchain and IoT in a green supply chain will further digitize and increase transparency in supply chains.

We have done a categorization of all barriers based on the expert survey by academicians and industry experts from industries in India. The concept map helps in identifying possible solutions for the challenges and initiatives to be taken for the smooth integration of technologies in the green supply chain.

We studied the relationship between job engagement and systematic problem solving (SPS) among shop-floor employees and how lean production (LP) and Internet of Things (IoT) systems moderate this relationship.

We collected data from a sample of 440 shop floor workers in 101 manufacturing work units across 33 plants. Because our data is nested, we employed a series of multilevel regression models to test the hypotheses. The application of IoT systems within work units was evaluated by our research team through direct observations from on-site visits.

Our findings indicate a positive association between job engagement and SPS. Additionally, we found that the adoption of lean bundles positively moderates this relationship, while, surprisingly, the adoption of IoT systems negatively moderates this relationship. Interestingly, we found that, when the adoption of IoT systems is complemented by a lean management system, workers tend to experience a higher effect on the SPS of their engagement.

One limitation of this research is the reliance on the self-reported data collected from both workers (job engagement, SPS and control variables) and supervisors (lean bundles). Furthermore, our study was conducted in a specific country, Italy, which might have limitations on the generalizability of the results since cross-cultural differences in job engagement and SPS have been documented.

Our findings highlight that employees’ strong engagement in SPS behaviors is shaped by the managerial and technological systems implemented on the shop floor. Specifically, we point out that implementing IoT systems without the appropriate managerial practices can pose challenges to fostering employee engagement and SPS.

This paper provides new insights on how lean and new technologies contribute to the development of learning-to-learn capabilities at the individual level by empirically analyzing the moderating effects of IoT systems and LP on the relationship between job engagement and SPS.

The purpose of this study is to determine the characteristics of the studies in terms of country, participant profile and methodology, as well as to determine what the Internet of Things (IoT) is currently contributing to higher education.

The study was developed following the methodology supported by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and the PICOS strategy, retrieving scientific literature from Web of Science, Scopus, ERIC and Google Scholar. Of the 237 studies that the search yielded, 11 were included.

The results showed that among the opportunities offered by IoT is that it not only brings the introduction of information and communication technology into the classroom, but also enhances student interest, thus, improving the quality of teaching in higher education. On the other hand, one of the challenges it faces is the attitude of teachers towards its adoption, as well as the level of digital competence of teachers.

This study presents how higher education institutions are including the IoT in their educational activities. The IoT refers to a network of digital interconnectivity between devices, people and the internet itself that enables the exchange of data between them, allowing key information about the use and performance of devices and objects to be captured to detect patterns, make recommendations, improve efficiency and create better user experiences.

Customer value perception of Internet of Things (IoT)-based services has not been studied in the context of a company’s readiness to adopt IoT technology. The purpose of this paper is to address this gap by indicating a research framing that combines insights from the IoT business model literature and customer perception of the value of such models and their drivers.

The interplay between a company’s IoT readiness and its perception of the value of IoT services is tested using a sample of 90 Eastern European business customers in a competitive business field. The conceptual framework described also examines relationships among constructs that refer to relationship quality. This study evaluates its quantitative sample using partial least squares path modeling.

Customers’ perceived value of IoT business models strongly relates to their digitalization capabilities and their own company’s innovativeness. When referring to disruptive technical offerings, existing trustful and satisfactory relationships cannot enhance the customer’s value perception.

The sample of Eastern European buyers is not representative of the majority of manufacturing companies. A randomized sample using other sources such as large industry databases could be useful. In addition, a replication of the study in other countries would allow for a cross-border validation of this study’s results.

This study suggests a detailed process that is based on a careful preselection of test customers working for innovative companies. A marketing communication approach must state clearly the benefits the buyers get in return for their sacrifice of sharing data.

Technology readiness refers to the user’s propensity to embrace and use new technologies. The results indicate that IoT readiness influences the successful launch of IoT-related business models. For managers, this study proposes a process to implement IoT-related business models.

This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.

Applying four technology acceptance theories (theory of planned behavior, technology acceptance model, pleasure-arousal-dominance theory and technology readiness index), the author uses deductive quantitative research to develop a model, explaining IoT adoption intentions. Administrated questionnaires are distributed in Egypt among generation-Z and millennials in malls. A total of 400 questionnaires are used for hypotheses testing, applying structural equation modeling (SEM) path coefficient analysis.

Results of this study show that attitude, dominance, perceived usefulness, innovativeness and insecurity impact consumers' IoT adoption intentions; subjective norms, perceived behavior control, pleasure, arousal, perceived ease, optimism and discomfort hold insignificant impact on consumers' IoT adoption intentions.

Exploring IoT facets and how these facets impact consumers' adoption intentions, this study helps grasp technology acceptance in theory and practice, guiding scholar and practitioners (e.g. IoT developers, retailers, marketers and other field experts) to consider consumers' mindset when developing, improving and marketing IoT.

The contribution stems from the incorporation of various frameworks used to explain technology acceptance. By studying several theories jointly, the research extracts and identifies a significant set of facets (technical and psychological) to build a comprehensive theory of IoT acceptance, showing consumers' IoT adoption is not entirely similar to adoption of other past innovations. This understanding allows marketers to focus on content that needs to be promoted to boost consumers' IoT purchase plans. Future researchers could replicate the results to IoT categories (e.g. home appliances, cars, healthcare, education, sportswear, etc.) to improve external validity of the findings, among other future research opportunities.

In the current dynamic business environment, Internet of Things (IoT) is employed by a number of companies in the logistics industry to achieve intelligent sorting, network optimization, real-time tracking and simplifying last-mile service. Although logistics entities are trying to introduce IoT into their business areas, users' perception of this new technology is still limited. This paper aims to develop a research model for the factors influencing the user adoption of IoT technology in the logistics industry.

In this study, based on the major theories on the application of new technologies such as technology acceptance model (TAM), technology–organization–environment (TOE) and innovation diffusion theory (IDT), a new research model was established to identify factors affecting customers' behavioral intention (BI) to adopt IoT technology provided by logistics companies. In addition, the authors surveyed unspecified customers of Cainiao Logistics Network, which is in charge of the logistics operation of Alibaba Group, China's largest e-commerce company, and tested the causality between the latent variables presented in the model using the structural equation model (SEM).

This empirical study shows that the support system of a logistics company and users' innovative propensity significantly affect perceived ease of use (PEOU) and BI for logistics services to which IoT technology is applied. It also presents that users' perceived security and enjoyment significantly affect perceived usefulness (PU) and BI. In addition, it was possible to confirm that the causal structure between variables suggested by TAM that PEOU has a significant effect on PU and BI, and PU has a substantial effect on BI.

Logistics companies should expand and upgrade technical support systems so that customers can flexibly accept logistics services with IoT technology and make efforts to alleviate customers' concerns about personal information leakage. In addition, it is necessary to find customers with an inclusive attitude toward using new technologies, to induce them to become leading users of logistics devices with IoT technology and to find various ways to amplify their enjoyment. Through a strategic approach to these technical and individual factors, it will be possible to boost customers' intention to use IoT logistics services.

As far as the authors know, this paper is the first study to set significant factors that affect users' BI to use IoT technology-applied logistics services provided by logistics companies and empirically analyze the causal relationships between proposed latent variables.

The Internet of Things (IoT) real-time data collection can help to more efficiently optimize and control companies' internal processes. Prior research analyzed IoT benefits and potential applications. Nevertheless, there is little empirical evidence and theoretical understanding of how IoT impacts new product development (NPD). This article aims at narrowing this gap.

In total, 54 case studies were selected from an IoT database – IoT ONE. IoT ONE has a section on NPD. NPD was divided into three phases: discovery, development and commercialization. The adopted IoT technology maturity level was also analyzed. A content analysis was carried out to identify the impacts of IoT in NPD.

This study’s findings capture the emerging patterns of IoT adoption and its impact on NPD. Of the total, 33 IoT adoption cases in the sample were in the machinery and equipment sector. Adopted technologies were at least two years old in 85% of the sample. Only 15% adopted cutting edge technologies (less than 2 years old). Key actors (e.g. vendors) facilitate IoT adoption. By a small margin, the larger impacts of IoT were in the commercialization phase, where it was primarily applied to improve and optimize production processes, to better execute and synchronize new products launching, and to increase the factories' productive capacity. In the discovery phase, IoT was mainly used to identify new opportunities in the market and to collect customer data, to generate a better customer experience. In the development phase, IoT allows greater integration across departments, increasing internal collaboration and allowing more flexible NPD.

Many articles studied the impact of information technologies in NPD. Few address the impact of IoT in NPD. IT tells about the impact of better communications with relevant people. IoT tells about machine acquired information and knowledge. This is new, much broader and deals with quite different impacts on NPD.

This study aims to suggest directions for innovation-driving paths for sustainable growth through an in-depth case analysis of a successful Internet of Things (IoT) in small- and medium-sized enterprise (SME) in South Korea. IoT is expected to play a significant role in the future industry 4.0 platform. Yet, little is known about how SMEs in the IoT industry (IoT-SMEs hereafter) pursue innovation in alignment with attributes inherent in the IoT.

This study addresses relatively unexplored key research questions on innovation strategies of IoT-SMEs. To do so, we employ an exploratory research methodology, along with an extensive review of the literature in the areas of the IoT, SMEs innovation and sustainable growth strategy. Specifically, we conduct intensive individual interviews to find IoT inherent innovation attributes and a case study to explore the process of linking these attributes to innovation-driving paths.

The analysis results reveal that there exist disruptive and open innovation attributes in the IoT industry that enable IoT-SMEs to enhance their structure and process related capabilities, to create business models for products and services and to collaborate with external parties in marketing to enter the market. We excavate practical insights into driving innovation based on IoT attributes and suggest enabling paths for pursuing innovation and entering overseas markets for IoT-SMEs.

This study investigates an underexplored significant area of research on the relationship between IoT attributes and innovation paths. The findings provide profound theoretical and practical implications. To the best of the author’s knowledge, it is the first attempt to link disruptive and open IoT attributes to innovation paths of IoT-SMEs. The results provide directions for pursuing effective innovation in responding to the IoT market for sustainable growth.