Unlocking consumer trust: Exploring key factors in blockchain-enabled traceability for processed food supply chain

Background: This study explores the key factors of blockchain-enabled traceability systems that influence consumer trust in the Indian processed food supply chain. The study provides crucial information for companies, managers and policymakers considering blockchain initiatives for food supply chain traceability and transparency. From an academic perspective, it bridges the knowledge gap between consumer trust and blockchain-enabled traceability. It also contributes to a better understanding and knowledge of the key trust-influencing factors of blockchain-enabled traceability systems.Materials and Methods: The study adopted a quantitative research approach, utilising a structured questionnaire for data collection. Exploratory factor analysis was employed to identify and analyse the trust-influencing factors of blockchain-enabled traceability systems. It provides empirical evidence that adopting a blockchain-enabled traceability system can enhance consumer trust.Results: The study revealed that consumers perceive “food authenticity”, “environmental sustainability”, “product traceability”, and “assured transparency” as significant trust-influencing factors in blockchain-enabled traceability systems for processed food products. The study encourages collaboration between food producers, retailers, and technology providers to develop a digital food supply chain.Conclusions: By harnessing blockchain-enabled traceability systems, the complexities of AFSC can be documented and stored in an immutable ledger, offering consumers unprecedented transparency and accountability. This fosters consumer trust by providing information on food origin, processing, and quality measures

Risk Managed Cloud Adoption: An ANP Approach

To meet the ever-increasing demand for offering a sustainable environment, organizations are beginning to aim for cloud adoption and the migration of their IT infrastructure and operations to the cloud, utilizing various cloud-based technologies. However, cloud adoption has been impeded by the risk of being exposed as a result of a variety of concerns, including performance, security, and privacy concerns, as well as vulnerabilities and data portability. As a result, this study was carried out to investigate and analyse a variety of risks that come with cloud computing adoption by estimating the impact and frequency of these hazards. In this study, the Analytical Network Process (ANP) is used to prioritise these hazards. Prioritization of these risks based on their influence on cloud adoption may be useful for organizations in building a corrective action plan. According to their negative influence on cloud adoption, "business continuity and recovery planning" and "poor availability of services" are shown to be the most prominent hazards. This research also found that the two most common dangers encountered by cloud adopters in India are "poor availability of services" and "slow response rate.

A step to clean energy - Sustainability in energy system management in an emerging economy context

Due to high consumption of energy, its associated concerns such as energy security and demand, wastage of resources, and material-energy recovery are leading to the importance of sustainable energy system development. This is a high time to assess the sustainability in energy systems for meeting the requirements of energy with an enhanced economic, ecological, and social performance from a nation context. The energy system plays a significant role in deciding the economic progress of emerging economies such as India, China, Brazil, and Africa. In this paper, an original attempt has been made to list and evaluate important indicators for sustainability assessment of energy systems development and management in an emerging economy especially India. Firstly, based on the analysis of the extant literature and then followed by expert opinion, potential key sustainability assessment indicators for energy systems development and management were identified. Further, grey based Decision-Making Trial and Evaluation Laboratory technique to understand the causal interactions amongst indicators and segregate them into cause and effect groups, is used. This work can provide useful aids to decision making bodies, sustainability practitioners and business organisations in selective implementation, monitoring and control of sustainable strategies in energy systems development and management and meeting sustainable development goals of clean energy in a nation context.N

Analysis of Factors Contributing to Economic Disruption Caused by COVID-19 in State of Odisha

The COVID-19 pandemic has had a devastating impact on the world, causing significant losses in life, employment, and work hours and wreaking havoc on the economies of many nations. A study was conducted to investigate the factors that contributed to Odisha's economic decline during the pandemic, which is one of India's states. The study surveyed 20,000 samples and employed the K-Mean clustering approach to identify six clusters. Each cluster was represented in a table. Lastly, the soft computing technique explored the property of interest

Blockchain Technology Applications in Healthcare Supply Chains—A Review

Understanding the prospective of blockchain technology and its uses in the healthcare sector is essential so that its considerable implementation can support the industry’s much-needed digitization. Furthermore, blockchain can provide answers to the issues in the healthcare industry today. Blockchain’s features like security, traceability, transparency, cost efficiency etc. can help bring supply chain transparency, health record management and prevent drug counterfeiting. Blockchain has emerged as a promising technology with great ability to bring changes to the healthcare sector. Therefore, this study aims to comprehend the current state of blockchain technology research in the healthcare supply chains. Further, it presents potential repercussions and the potential routes it may open for future research initiatives in this area. A systematic literature (SLR) process has been used and conducted in two stages. In the first stage, articles were identified through literature search and were subjected to keyword selection, database search and screening process. Finally, 124 papers were categorized through bibliographic coupling. A detailed investigation of these included papers was performed in the second stage with descriptive and content analysis. The results reveal that research related to blockchain applications or implementation is at a nascent stage. The publications in this area have been rising steadily over the past few years. When it comes to publishing in this field, India is the most productive nation while IEEE Access is the most productive journal. Applications for blockchain technology in healthcare include medical insurance, remote patient monitoring, medication supply chain management, electronic health records (EHRs), and more. The most popular use case is EHR management. The analysis further conveys that findings are less generalizable due to more theoretical or less empirically designed studies published in this domain. This study will help stakeholders, policymakers, researchers, and managers in taking strategic decisions regarding the adoption of the technology in the healthcare industry. This study is done concerning the blockchain’s use in the healthcare sector context, so other emerging technologies and sectors not taken must be considered while generalizing the results. This study is among the few up-to-date consolidated attempts to present a systematic literature review and bibliometric analysis for assessing blockchain technology’s potential in the healthcare sector. It provides an overview of the published work with implications and proposed cluster-wise future research directions

Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Purpose: The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist among those obstacles. Design/methodology/approach: A combination of a review of the relevant literature and consultation with subject matter experts is used to identify the barriers to widespread adoption of mHealth. The identified barriers are then analysed using an Interpretive Structural Modelling (ISM) technique to study the interplay existing among them and represent these in a hierarchical manner. Findings: The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the MICMAC investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies, and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications. Practical implications: Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted. Originality/Contributions: At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learned the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice

Blockchain technology for enhancing supply chain performance and reducing the threats arising from the COVID-19 pandemic

The blockchain is expected to radically alter people’s real-time interactions and transactions, culminating in the birth of a new economy in a digital era [...

Integrated approach of fuzzy multi-attribute decision making and data mining for customer segmentation

This research work focuses on integrating the multi attribute decision making with data mining in a fuzzy decision environment for customer relationship management. The main objective is to analyse the relation between multi attribute decision making and data mining considering a complex problem of ordering customers segments, which is based on four criteria of customer’s life time value, viz. length (L), recency (R), frequency (F) and monetary value (M). The proposed integrated approach involves fuzzy C-means (FCM) cluster analysis as data mining tool. The experiment conducted using MATLAB 12.0 for identifying eight clusters of customers. The two multi attribute decision making tools i.e., fuzzy AHP (Analytic Hierarchy Process) and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) are used for ranking these identified clusters. The applicability of the integrated decision making technique is also demonstrated in this paper considering the case of Indian retail sector. This research collected responses from nine experts from Indian retail industry regarding their perception of relative importance of four criteria of customer life value and evaluated weights of each criterion using fuzzy AHP. Transaction data of 18 months of the case retail store was analysed to segment 1,600 customers into eight clusters using fuzzy c-means clustering analysis technique. Finally, these eight clusters were ranked using fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The findings of this research could be helpful for firms in identifying the more valuable customers for them and allocate more resources to satisfy them. The findings will be also helpful in developing different loyalty program strategies for customers of different clusters