Development of IoT based data-driven agriculture supply chain performance measurement framework

Exploring the application of ICTs in decarbonizing the agriculture supply chain: A literature review and research agenda

The contemporary agricultural supply chain necessitates the integration of information and communication technologies to effectively mitigate the multifaceted challenges posed by climate change and rising global demand for food products. Furthermore, recent developments in information and communication technologies, such as blockchain, big data analytics, the internet of things, artificial intelligence, cloud computing, etc., have made this transformation possible. Each of these technologies plays a particular role in enabling the agriculture supply chain ecosystem to be intelligent enough to handle today's world's challenges. Thus, this paper reviews the crucial information and communication technologies-enabled agriculture supply chains to understand their potential uses and contemporary developments. The review is supported by 57 research papers from the Scopus database. Five research areas analyze the applications of the technology reviewed in the agriculture supply chain: food safety and traceability, security and information system management, wasting food, supervision and tracking, agricultural businesses and decision-making, and other applications not explicitly related to the agriculture supply chain. The study also emphasizes how information and communication technologies can help agriculture supply chains and promote agriculture supply chain decarbonization. An information and communication technologies application framework for a decarbonized agriculture supply chain is suggested based on the research's findings. The framework identifies the contribution of information and communication technologies to decision-making in agriculture supply chains. The review also offers guidelines to academics, policymakers, and practitioners on managing agriculture supply chains successfully for enhanced agricultural productivity and decarbonization.

Disruptive supply chain technology assessment for sustainability journey: A framework of probabilistic group decision making

The fourth industrial revolution, commonly recognized as Industry 4.0, has been ushered by modern and innovative intelligence and communication technologies. Concerns about disruptive technologies (DTs) are beginning to grow in developing countries, despite the fact that the trade-offs between implementation difficulties and realistic effects are still unknown. Hence, prioritization and promotion of such technologies should be considered when investing in them to ensure sustainability. The study aims to provide new critical insights into what DTs are and how to identify the significant DTs for sustainable supply chain (SSC). Understanding the DTs' potential for achieving holistic sustainability through effective technology adoption and diffusion is critical. To achieve the goal, an integrated approach combining the Bayesian method and the Best Worst Method (BWM) is utilized in this study to evaluate DTs in emerging economies' supply chain (SC). The systematic literature review yielded a total of 10 DTs for SSC, which were then evaluated using the Bayesian-BWM to explore the most critical DTs for a well-known example of the readymade garment (RMG) industry of Bangladesh. The results show that the three most essential DTs for SSC are "Internet of things (IoT)", "Cloud manufacturing", and "Artificial intelligence (AI)". The research insights will facilitate policymakers and practitioners in determining where to concentrate efforts during the technology adoption and diffusion stage in order to improve sustainable production through managing SC operations in an uncertain business environment.

A review of supply chain quality management practices in sustainable food networks

Supply chain quality management practices are necessary to improve processes, meet consumer quality needs, and enhance supply chain quality management performance in sustainable food networks. Food supply chain quality management and associated practices are considerably studied in global food systems, less so for alternative food networks. There are salient differences between global food systems and alternative food networks, which may reflect on the applicable supply chain quality management practices in the food systems and networks. This paper reviews the literature on supply chain quality management practices, with a focus on alternative food networks. A systematic literature review methodology is adopted, resulting in the analysis of seventy-eight papers, identifying a total of one hundred and three supply chain quality management practices. The identified supply chain quality management practices were analysed in relation to their link to a) place, production, and producer and b) link to (bio)processes. Emerging themes from the analysis are discussed, and some areas of future research were put forward.

GIANN—A Methodology for Optimizing Competitiveness Performance Assessment Models for Small and Medium-Sized Enterprises

The adoption of models based on key performance indicators to diagnose and evaluate the competitiveness of companies has been presented as a trend in the operations’ management. These models are structured with different variables in complex interrelationships, making diagnosis and monitoring difficult due to the number of variables involved, which is one of the main management challenges of Small and Medium-sized Enterprises. In this sense, this article proposes the Gain Information Artificial Neural Network (GIANN) method. GIANN is a method to optimize the number of variables of assessment models for the competitiveness and operational performance of Small and Medium-sized Enterprises. GIANN is a hybrid methodology combining Multi-attribute Utility Theory with Entropy and Information Gain concepts and computational modeling through Multilayer Perceptron Artificial Neural Network. The model used in this article integrates variables such as fundamental points of view, critical success factors, and key performance indicators. GIANN was validated through a survey of managers of Small and Medium-sized Enterprises in Southern Brazil. The initial model was adjusted, reducing the number of key performance indicators by 39% while maintaining the accuracy of the results of the competitiveness measurement. With GIANN, the number of variables to be monitored decreases considerably, facilitating the management of Small and Medium-sized Enterprises.

Modeling the Sustainable Supply Chain Network Design for Food-Agricultural Industries considering Social and Environmental Impacts

The food supply chain is one of the most sensitive supply chains as it is directly related to the health of humans and society. Therefore, this study aims to evaluate the components of the sustainable supply chain in the food industry. For this purpose, in the first step, several studies and research backgrounds have been conducted by researchers to identify the effective index on sustainability in the food and agricultural supply chain. After reviewing the literature, general indicators of sustainability that affect the agricultural supply chain are specified. Next, by using the fuzzy DEMATEL method, the effectiveness and efficiency of these criteria in three economic, environmental, and social dimensions have been assessed. The results show that in the economic dimension, the use of high technology in the production and the presentation of various citrus forms by using intermediate and conversion industries is the most effective. Criteria for purchasing and using livestock manure instead of using chemical fertilizers have a very high level of effectiveness. In the environmental dimension, reducing or eliminating waste production using recyclable and environmentally friendly materials has the most significant impact. In the social dimension, the positive mental image of customers has a more positive approach to manufacturers who use a sustainable supply chain and has the most impact. The main achievement of this study is that the most important factor in sustainability is the citrus quality control of the agricultural supply chain.

Enablers for resilience and pandemic preparedness in food supply chain

The recent COVID-19 pandemic has caused enormous disruptions to supply chain (SCs). Border restrictions forced countless businesses to close either permanently or temporarily. However, the food industry is an essential sector that needs to be operational during a pandemic. Although the food industry has proactively worked towards fulfilling human needs, the food supply chain (FSC) faced numerous challenges, forcing SC managers to rethink their business strategy to cater to consumer demands effectively. In a pandemic situation, manufacturing operations need to repurpose and adapt to produce different high-demand products. Resilience initiatives help fight disruption phases in an uncertain environment by building capacity to resist and recover to a better position. This study identifies 14 key enablers to develop a resilient FSC and reveals the most significant enablers in India. We used a hybrid Delphi-interpretive structural modeling (ISM) and Fuzzy decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) methodology to achieve these goals. The Delphi technique identified essential enablers, while the ISM analyzed the interrelationship among enablers and level of importance in a hierarchical structural model. Finally, the Fuzzy-DEMATEL categorized the enablers into the cause-effect group. This study helps SC decision-makers recognize the enablers and the contextual and causal relationships to improve resilience initiatives. It also helps them repurpose their manufacturing operations and shift to other highly required and high-demand production.

Towards Convergence of IoT and Blockchain for Secure Supply Chain Transaction

Supply chain management (SCM) is essential for a company’s faster, efficient, and effective product life cycle. However, the current SCM systems are insufficient to provide product legitimacy, transaction privacy, and security. Therefore, this research proposes a secure SCM system for the authenticity of the products based on the Internet of Things (IoT) and blockchain technology. The IoT-enabled Quick Response (QR) scanner and the blockchain-integrated distributed system will allow all the SCM stakeholders to begin secure and private transactions for their products or services. Resulting, the consumer will receive an authentic and genuine product from the original producer. A lightweight asymmetric key encryption technique, i.e., elliptic curve cryptography (ECC) and Hyperledger Fabric-based blockchain technology with on-chain smart contracts are applied for distributed IoT devices to make the authentication process faster and lighter. Each SCM stakeholder is registered by the service provider and receives corresponding public and private keys, which will be used for the authentication process of the participants and IoT devices. The authenticated QR scanner records all transactions on the blockchain. Consequently, there will be no human intervention for the SCM transactions. The security and scalability analysis demonstrates that the proposed system is more secure and robust than other state-of-the-art techniques.

Technology-Driven Responsiveness in Times of COVID-19: A Fuzzy Delphi and Fuzzy AHP-Based Approach

Supply chain responsiveness creates value for firms and their stakeholders and is a key towards generating above-normal profits for firms. Consequently, there has been a surge of research on it, which has expanded due to the pressures to be responsive during the pandemic of COVID19. Responsiveness is an attribute wherein the supply chains are equipped to respond resolutely and within a suitable timeframe to consumer requirements. The trouble to businesses posed by COVID-19 caught several firms off-guard. Further, there is limited research on the augmentation of supply chain responsiveness through new technologies. The present research, therefore, applies a hybrid approach by combining fuzzy Delphi and fuzzy AHP to understand the technology-driven enablers of supply chain responsiveness by employing a case company in food retail. The investigation reveals that supply chain integration technologies, sustainable manufacturing technologies, and smart warehousing are the most important enablers of supply chain responsiveness in the context of food supply chains. The results aid the key enablers that need attention and resources to be directed towards these enablers to eliminate a chance of missing on a successful transition into a more responsive supply chain.

Integrated technologies toward sustainable agriculture supply chains: missing links

Purpose

This article sheds light on the missing links concerning the study of using integrated enabling technologies toward sustainable and circular agriculture supply chains by examining the available literature and proposing future research possibilities.

Design/methodology/approach

The relevant literature was researched through online databases such as Scopus, Web of Science, Academic Search Premier, Emerald, IEEE Xplore, Science Direct, World Scientific Net and Springer-Link Journals, covering a period from 1999 to 2020. A systematic literature review based on 75 papers analyzed the integration of the concepts of enabling technologies, sustainability, circular economy and supply chain performance in agriculture supply chains.

Findings

It was identified that enabling technologies and agriculture supply chains alone have been explored further than integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains. Enabling technologies and agriculture supply chains' main findings are: enabling technologies have been studied to improve food safety, food quality and traceability in agriculture supply chains. The main results regarding integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains are: Internet of Things and information communication technology play an important role in addressing food security, traceability and food quality, which help achieve sustainable development goals.

Originality/value

This review study provides 13 research questions to underpin future trends regarding integrated technologies' application in agriculture supply chains for circular and sustainable growth.

The interplay between the Internet of things and supply chain management: challenges and opportunities based on a systematic literature review

Purpose

This study aims to identify and analyze how Internet of things (IoT) technology affects supply chain management (SCM) performance.

Design/methodology/approach

A systematic literature review was conducted (using Scopus, JSTOR, Emerald, ProQuest, Science Direct and Web of Science) covering a 20-year timeframe (2000–2020). Out of 2,572 papers identified, 171 peer-reviewed papers from the most important journals were selected. Content analysis was used following the Global Supply Chain Forum (GSCF) SCM framework.

Findings

Regarding the GSCF SCM framework processes, most IoT-based studies have addressed improving order fulfilment, manufacturing flow management and demand management processes. However, no studies addressing the Supplier relationship management process were identified, suggesting that IoT-based applications are perceived to add more value in downstream than upstream SCM processes. The importance of using enabling technologies to realize the potential of value generation of IoT was also revealed. Findings suggest new research avenues related to product development and commercialization process, the supplier relationship management process, the returns management process, servitization strategies, new SCM models and new business models.

Research limitations/implications

The review encompasses only academic papers from journals considered the most relevant (retrieved from specific databases), using the impact factor as the quality criterion.

Practical implications

The findings can help business managers better understand the potential of IoT technology, such as the main applications identified in the literature and their impacts on SCM processes. Their importance in enabling technologies to leverage SCM performance is identified and the emerging SCM models/business models that IoT deployment can enable are highlighted.

Originality/value

This study contributes to filling a gap in the literature using a systematic literature review of how IoT technology affects SCM performance through content analysis, using an SCM framework to clarify which SCM processes are affected. Academic articles from the most important journals from 2000 to 2020 are identified.

A systematic and network-based analysis of data-driven quality management in supply chains and proposed future research directions

Purpose

This work aims to review past and present articles about data-driven quality management (DDQM) in supply chains (SCs). The motive behind the review is to identify associated literature gaps and to provide a future research direction in the field of DDQM in SCs.

Design/methodology/approach

A systematic literature review was done in the field of DDQM in SCs. SCOPUS database was chosen to collect articles in the selected field and then an SLR methodology has been followed to review the selected articles. The bibliometric and network analysis has also been conducted to analyze the contributions of various authors, countries and institutions in the field of DDQM in SCs. Network analysis was done by using VOS viewer package to analyze collaboration among researchers.

Findings

The findings of the study reveal that the adoption of data-driven technologies and quality management tools can help in strategic decision making. The usage of data-driven technologies such as artificial intelligence and machine learning can significantly enhance the performance of SC operations and network.

Originality/value

The paper discusses the importance of data-driven techniques enabling quality in SC management systems. The linkage between the data-driven techniques and quality management for improving the SC performance was also elaborated in the presented study.

Application of Lifecycle Measures for an Integrated Method of Environmental Sustainability Assessment of Radio Frequency Identification and Wireless Sensor Networks

Internet of Things (IoT) technology has advanced in recent years, leading to improvements of manufacturing processes. As a result of such improvements, environmental sustainability assessments for technologies have been requested by international control agencies. Although various assessment approaches are widely applied, IoT technology requires effective assessment methods to support the decision-making process and that incorporate qualitative measures to create quantifiable values. In this paper, a new environmental sustainability assessment method is developed to assess radio frequency identification (RFID) and wireless sensors networks (WSN). This integrated assessment method incorporates a modified and redesigned conceptual methodology based on technical project evaluation (IMATOV) and an extension of conventional lifecycle measures. The results shows the most and least important metrics. The most important metrics are the categories “electronic devices disposed of completely” and “decrease in stocks”, with the greatest GWFs (20% and 19%, respectively) and IAVs (127% and 117%, respectively) and moderate consolidated degrees of fulfillment. Relatively low degrees of fulfillment are achieved by categories such as “decrease in numbers of assets”, “supply chain echelons benefiting RFID”, and “tag lifecycle duration”, with IAVs below 10%. This study promotes an integrated method to support decision-making processes in the context of environmental sustainability assessments based on lifecycle measures.

The internet of things in the food supply chain: adoption challenges

Purpose

The food supply chain (FSC) challenges coupled with global disruptions, such as the recent coronavirus disease 2019 (COVID-19) pandemic outbreak, exacerbate its vulnerability. The Internet of things (IoT) is one of the disruptive technologies being adopted in food supply chain management (FSCM). This study aims to address the challenges of IoT adoption in the FSC by systematically analyzing the prior pertinent literature.

Design/methodology/approach

A structured literature review was used to collate a list of peer-reviewed and relevant publications. A total of 72 out of 210 articles were selected for the final evaluation.

Findings

The literature review findings suggest five themes: technical, financial, social, operational, educational and governmental related challenges. A total of 15 challenges were devised from the review related literature of IoT adoption. The study concludes with future research recommendations for scholars and practical implications for practitioners.

Research limitations/implications

While this study focuses on the overall FSC, further research should address other domains in the FSC such as cold supply chain, agriculture and perishable food to gain a better contextual understanding of the specific case.

Originality/value

The topic of IoT adoption in the FSCM is still considered emerging. Therefore, the present work contributes to the limited studies and documentation on the level of IoT implementation in the FSCM. This study should help organizations to assimilate how to adopt and manage the IoT application by addressing the factors and challenges presented in this research.