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This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to support the main factors likely to affect CSC. This proposed model combines the most well-known digital tools such as blockchain technology, Internet of Things (IoT) and cloud computing (CC).

Motivated by its effective solution to enhance trust, traceability, transparency and minimize costs and risks, the combination of the most well-known digital tools such as blockchain technology, IoT and CC to develop a new digital CSC model is addressed in this research. This study first investigates and conducts a deep review analysis that explores how Industry 4.0 technologies can enable collaboration mechanisms. Second, based on an analysis of literature review, the main factors likely to affect CSC have been identified and analysed. Finally, the authors combine digital tools to support the identified factors to enhance transparency, traceability and trust by proposing a new digital CSC model. This proposed model will be used as a referential guide to encourage and motivate SC actors to collaborate in digital CSC.

This work provides many important contributions to theory and practice. First, role and impacts of the most well-known digital tools such as blockchain technology, IoT and CC for digitizing CSC have separately presented and developed. Second, the authors conceptualized a framework by developing a new digital CSC model. This conceptual digital model can be used as a referential guide for all SC actors in order to motivate them to collaborate in a modern, intelligent, secure and reliable SC. It can also support all factors affecting CSC.

The originality of this study is first investigating separately the roles and impacts of each digital tool on CSC performance. Second, the authors combine the most well-known digital tools such as blockchain technology, IoT and CC in order to develop an efficient, smart, modern and new digital CSC model. In this combination, CC is used as platform as a service enabling to link and connect the blockchain and IoT to support the main factors affecting CSC. Unlike to digital CSC model with only one digital tool, the proposed model is more realistic since depending on the information to be shared with other actors, the most appropriate tool will be automatically detected and used. This solution offers a large choice to SC actors for real time data and information sharing. In addition, the proposed model will largely enhance traceability, transparency and trust in CSC.

This study investigates the enablers and challenges of digital supply chains (DSCs) adoption and develops a digital supply chain maturity (DSCM) model as a basis for developing guidelines for DSC adoption in the digital transformation journey.

The research involves a systematic literature review (SLR) of Industry 4.0 (I4) adoption in supply chain (SC) practices to identify key enablers and associated maturity levels. The literature search of published articles during the 1997–2020 period and subsequent screening resulted in 64 articles. A DSCM model was developed using the categorization of important enablers and associated levels transitioning from the traditional SC to the DSC ecosystem.

Four broader categories of DSC enablers and challenges were identified from the content analysis of SLR. Digital strategy alongside I4 technologies and human capital were prominent in DSC adoption as I4 technologies and human capital depend on other enablers such as dynamic capabilities (DCs). Lack of infrastructure and financial constraints to implementing I4 were significant challenges in the DSC adoption.

The proposed DSCM model provides a holistic view of enablers and maturity levels from traditional SC to DSC adoption. However, the DSCM model needs to be empirically validated and streamlined further using inputs from practitioners.

The proposed DSCM model can be used as a framework to guide practitioners in assessing maturity and developing implementation plans for successful DSC adoption.

This research introduces a novel DSC maturity model through a holistic view of enablers and maturity levels from traditional SC to DSC adoption.

Agriculture is one sector where the Internet of things (IoT) is expected to make a major impact. Yet, its adoption in the sector falls behind expectations. The purpose of this paper is to present the state-of-the-art of IoT in agriculture and investigate its slow adoption in the sector.

The authors have undertaken a systematic review and a synthesis of 1355 relevant publications over the last decade.

This literature review reveals that the “big three” barriers for the overall sector are cost, skills and standardization. The lack of connectivity and data governance are two key reasons why most of the proposed IoT solutions are standalone systems of limited scope, while the majority of commercial IoT efforts focus on practices in the protected indoor environment. Lastly, the analysis of past research along the five layers of the IoT system architecture reveals limited attention to barriers and solutions at the business layer, which represents a research opportunity for information systems scholars.

It is possible that some of relevant publications were missed in the literature search, although the search queries were kept as broad as possible to avoid the exclusion of any relevant work. Any publication written in any other language other than English was excluded from the review. Given the geographical distribution of the reviewed English publications (see section 4.1), it is highly likely that important works written by Chinese and European scholars in their native language were overlooked.

This study provides practical insights into the technical and organisational challenges on the ground. It is the hope that this literature review lays the groundwork for IS researchers who are well positioned to investigate technology adoption challenges in the relatively understudied agriculture sector.

To the best of the authors’ knowledge, this is the first comprehensive review of adoption barriers and solutions across all five layers of the IoT system architecture.

Supply chain integration (SCI) dominates supply chain strategy and is receiving increasing academic attention. The purpose of this paper is to provide a systematic review of the knowledge trajectory and structure of the SCI field.

Based on 3,533 papers extracted from the Web of Science (WoS), this paper adopts the main path analysis (MPA) method to detect three distinct knowledge development trajectories. Coupling-based clustering is combined with MPA to reveal three critical subfields.

The findings show that the definition, content and dimensions of SCI lack unified conclusions. The influencing factors and performance consequences of SCI are long-standing research elements. Building theoretical models and integrated systems and applying blockchain technology to improve SCI are the key research contents. The intertwining of collaboration and SCI cannot be ignored, and the green SCI may be a hot topic in the future.

This study explores knowledge in the SCI field based on the limited literature collected by WoS rather than all published papers. The omissions of some relevant papers and books may exist.

The study methodology provides a framework for similar studies in the future, and the results help researchers to get a comprehensive picture of the knowledge trajectory and structure of the SCI field.

Compared to existing reviews, MPA combines cluster analysis to develop a synthetic framework of the knowledge trajectory and structure in the SCI domain. It contributes to a systematic review of the development of SCI.

Enterprise information systems (EISs) are intricate technological artifacts with wide user base within organizations. While much is known about the adoption and implementation of EISs, little is known about what subsequently follows them, i.e. the assimilation of EISs. This article aims to examine the assimilation of the EISs which is consequential to realizing any benefits from such enterprise technology.

The author conceptually draws on the insights from the expectation confirmation theory, theory of reasoned action, equity theory, and prospect theory to examine the assimilation of the EISs. In doing so, the author generates competing testable hypotheses regarding the relationship between individual users' psychological and social influences through expectation (dis)confirmation and the users' intention to assimilate the EISs.

By conceptually articulating the individual users' psychological and social influences through expectation (dis)confirmation, the author offers a more complete account of the assimilation of EISs, and provide several avenues for future empirical and theoretical research on enterprise technology assimilation.

The extant research that there is on the assimilation of the EISs focuses more on the organizational – as opposed to individual – level determinants of EISs assimilation and largely considers the functional – rather than psychological and social – drivers. This article addresses these important, yet understudied, factors to offer a more nuanced account of EISs assimilation.

Information asymmetry and poor solvency caused by uncertainties in supply chains are the root causes of supply chain financing risks (SCFR). The purpose of this paper is to explore the effect of supply chain integration on reducing SCFR by incorporating the mechanisms of information sharing and controlling supply chain risks (SCR).

This paper proposes hypothesis to discuss the impact of integration on SCFR and the mediating roles of alleviating information asymmetry and mitigating SCR, aiming at discovering factors and mechanisms to reduce SCFR. The research model was validated by applying structural equation modeling on survey data from 321 Chinese small and medium-sized enterprises (SMEs).

Integration significantly reduces SCFR by dual approaches of information sharing and mitigating SCR, confirming that alleviating information asymmetry to reach information transparency and controlling SCR to reduce uncertainties facilitate less SCFR.

SMEs should enhance integration capability to reduce SCFR as it greatly influences the evaluation of financial service providers on SMEs and the sustainable financing capacity of SMEs. Additionally, any other methods that can improve information sharing and reduce SCR should be attached if possible.

This study represents a pioneering attempt to analyze the impact of integration on reducing SCFR by exploring the specific mechanisms of alleviating information asymmetry and mitigating SCR. Meanwhile, few prior empirical studies have highlighted the importance of SCFR.

This paper studies early stages of actor mobilization for institutional change within Swedish esports.

The authors employ interpretative phenomenological analysis.

The authors’ findings explain how actors become motivated to act in critical reflections linked to conflicting legitimacy judgments and emotionally charged personal struggles. Moreover, the findings show how, as actors get activated in collective action, they identify efficacy lines around valid domains and experience emotionally charged collective endeavors. Furthermore, the findings explain how particularities in early experiences project legitimacy aspirations that orient collective action toward validity ends and particular values and ideals shaping actors' grassroots movements.

This study adds to legitimacy and institutional change theory through individual actors' perspectives, providing key insights into how they are motivated, activated, and oriented. This study is the first to investigate grassroots activists' personal stories in esports.

This paper aims to study the economic effects of Cloud Computing for a sample of Israeli firms. The authors propose a framework that considers how this technology affects firm performance also introducing the indirect economic effects that take place through cloud-complementary technologies such as Big Data and Machine Learning.

The model is estimated through structural equation modeling. The data set consists of the microdata of the survey of information and communication technologies uses and cyber protection in business conducted in Israel by the Central Bureau of Statistics.

The results point to Cloud Computing as a crucial technology to increase firm performance, presenting significant direct and indirect effects as the use of complementary technologies maximizes its impact. Firms that enjoy most direct economic gains from Cloud Computing appear to be the smaller ones, although larger enterprises seem more capable to assimilate complementary technologies, such as Big Data and Machine Learning. The total effects of cloud on firm performance are quite similar among manufacturing and service firms, although the composition of the different effects involved is different.

This paper is one of the very few analyses estimating the impact of Cloud Computing on firm performance based on country microdata and, to the best of the authors’ knowledge, the first one that contemplates the indirect economic effects that take place through cloud-complementary technologies such as Big Data and Machine Learning.

Artificial intelligence (AI) is the most progressive commodity among current information system applications. In-house development and sales of beneficial products are difficult for many software development and service companies (SDSCs). SDSCs have some implicit concerns about implementing AI software development due to the complexity of AI technology; they require an evaluation framework to avoid development failure. To fill the void, this study identified the factors influencing SDSCs when developing AI software development.

Based on complex adaptive systems theory, three aspects were developed as the main factors of hierarchy, namely, employees' capabilities, environmental resources and team capabilities. Fuzzy analytic hierarchy process (FAHP) was used to assess the SDSCs' attitude. Based on SDSCs, attitudes toward implementing AI software projects were collected to calculate the hierarchy of factors.

The outcome of FAHP is used as understanding the key factors of SDSCs for selecting an AI software project, toward the improvement of overall project planning. Employees' stress resistance was considered as a priority for the project, although professional AI skills and resources were also important.

This study suggested three variables developed using complex adaptive systems. This study contributes to a better understanding of the critical aspects of developing AI software projects in SDSCs. The study's findings have practical and academic implications for SDSCs and subsequent academic development, broadening the scope of AI software development research.

The purpose of this study is to examine how the implementation of edge computing can enhance the progress of the circular economy within supply chains and to address the challenges and best practices associated with this emerging technology.

This study utilized a streamlined evaluation technique that employed Latent Dirichlet Allocation modeling for thorough content analysis. Extensive searches were conducted among prominent publishers, including IEEE, Elsevier, Springer, Wiley, MDPI and Hindawi, utilizing pertinent keywords associated with edge computing, circular economy, sustainability and supply chain. The search process yielded a total of 103 articles, with the keywords being searched specifically within the titles or abstracts of these articles.

There has been a notable rise in the volume of scholarly articles dedicated to edge computing in the circular economy and supply chain management. After conducting a thorough examination of the published papers, three main research themes were identified, focused on technology, optimization and circular economy and sustainability. Edge computing adoption in supply chains results in a more responsive, efficient and agile supply chain, leading to enhanced decision-making capabilities and improved customer satisfaction. However, the adoption also poses challenges, such as data integration, security concerns, device management, connectivity and cost.

This paper offers valuable insights into the research trends of edge computing in the circular economy and supply chains, highlighting its significant role in optimizing supply chain operations and advancing the circular economy by processing and analyzing real time data generated by the internet of Things, sensors and other state-of-the-art tools and devices.