Mohamed Abdel Basset, Mai Mohamed, Arun Kumar Sangaiah and Vipul Jain
Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is…
Abstract
Purpose
Strategic planning is an organization’s process of describing its strategy, or direction, and making decisions on allocating its resources to track this strategy. SWOT analysis is one of the most commonly used techniques for strategic planning. SWOT examines the strengths (S) and weaknesses (W) agents of the community together with opportunities (O) and threats (T), for selecting and implementing the best strategy which helps in achieving its goals. The purpose of this paper is to enhance the performance of SWOT analysis regarding the quantitative side of strategies, select the best strategy from different strategies and deal effectively with vague and incompatible information, which occurs usually in actual life.
Design/methodology/approach
This study used the neutrosophic analytic hierarchy process (AHP) incorporated with SWOT analysis.
Findings
By adding the neutrosophic AHP to SWOT analysis, the performance of SWOT analysis is enhanced through determining the quantitative values and dealing with vague and inconsistent information effectively leading to improved decisions.
Research limitations/implications
The developed integrated methodology is validated in a real-life case of Starbucks company. For the case study of Starbucks company, the proposed model helps in determining different strategic plans and, further, ranking these plans effectively, which will help the company to compete with its competitors and develop itself by obtaining a competitive advantage over its competitors in an uncertain business environment.
Practical implications
In the case study of Starbucks company, the proposed model helps to determine the different strategic plans, rank these plans which help the company compete with its competitors, develop itself and grow.
Originality/value
This research is the first to address SWOT analysis with neutrosophic AHP.
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Mohamed Abdel-Basset, Laila A. Shawky and Arun Kumar Sangaiah
The purpose of this paper is to present a comparison between two well-known Lévy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA).
Abstract
Purpose
The purpose of this paper is to present a comparison between two well-known Lévy-based meta-heuristics called cuckoo search (CS) and flower pollination algorithm (FPA).
Design/methodology/approach
Both the algorithms (Lévy-based meta-heuristics called CS and Flower Pollination) are tested on selected benchmarks from CEC 2017. In addition, this study discussed all CS and FPA comparisons that were included implicitly in other works.
Findings
The experimental results show that CS is superior in global convergence to the optimal solution, while FPA outperforms CS in terms of time complexity.
Originality/value
This paper compares the working flow and significance of FPA and CS which seems to have many similarities in order to help the researchers deeply understand the differences between both algorithms. The experimental results are clearly shown to solve the global optimization problem.
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Prasad G., Abishek P. and Karthick R.
The purpose of this paper is to discuss the special applications of unmanned aerial vehicles (UAVs) for the transport of medical goods.
Abstract
Purpose
The purpose of this paper is to discuss the special applications of unmanned aerial vehicles (UAVs) for the transport of medical goods.
Design/methodology/approach
Experimental work has been carried out to predict the performance characteristics of UAVs.
Findings
The results have been obtained to predict the range and endurance of UAVs, which can be optimized based on the payload and source of power.
Originality/value
Real-time applications. As the medical products are necessary in the real time life saving events.
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Li Cui, Meihua Gao, Jing Dai and Jian Mou
Collaboration is an important emerging dimension of sustainable supply chain management. How to improve supply chain collaboration (SCC) by means of operational excellence…
Abstract
Purpose
Collaboration is an important emerging dimension of sustainable supply chain management. How to improve supply chain collaboration (SCC) by means of operational excellence approaches has become an important research topic. The Internet of things (IoT), an important means of operational excellence, has also received increased attention. For better collaboration by the IoT, this study proposes a novel methodology to evaluate the measures of IoT adoption in SCC.
Design/methodology/approach
Based on the six-domain model and the common classification of collaboration, the measures of the IoT and the criteria of SCC are developed, respectively. A hybrid multi-step methodology that combines neutrosophic set theory, analytic hierarchy process (AHP) and technology for order preference by similarity to an ideal solution (TOPSIS) is proposed to complete the evaluation.
Findings
The results show that improving information transparency, strengthening the integration of management information systems and improving large data processing abilities are the most important measures of the IoT in improving SCC. Measures such as introducing sensing technology and laser scanning technology rank at the bottom and are relatively unimportant.
Practical implications
The research results provide insights and references for firms to improve SCC by adopting appropriate IoT measures.
Originality/value
Most of existing studies indicate the significance of technology in SCC. But this study shows a different conclusion that technologies rank the bottom, while information transparency is more important. And a suitable explanation is given. It further enriches the theoretical studies in SCC field.
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Anubha Anubha, Govind Nath Srivastava and Daviender Narang
The Metaverse and Internet of Things (IoT) have emerged like a tidal wave, and it is creating a transformative impact on society and industry. The metaverse and IoT changed the…
Abstract
The Metaverse and Internet of Things (IoT) have emerged like a tidal wave, and it is creating a transformative impact on society and industry. The metaverse and IoT changed the way companies were operating earlier and customers were living their lives. On the other hand, Metaverse enriches the customer experience by offering a matchless virtual experience using augmented reality and state-of-the-art technology. The metaverse and the IoT can be used in various sectors such as manufacturing, transportation, retailing, health care, banking, and automobiles to make cities smart. Metaverse and IoT provide real-time data, reduces operational cost and errors, improves efficiency, and helps industries to make intelligent decisions. Although the IoT and Metaverse offer significant benefits, it is not free from limitations. Ethical dilemmas, privacy issues, data breaches, and difficulty in extracting relevant data impose serious challenges that need to be addressed. There is an urgent and dire need to create a trade-off between the interest of the business and the privacy and security of customers. This chapter aims to discover the potential of Metaverse and IoT in various sectors (e.g., healthcare, transportation, and electronics). This study will bring significant insights to researchers and policymakers by exploring the likely benefits of IoT and metaverse in diverse sectors to develop smart cities. This chapter will also explain the challenges of metaverse and IoT, which can be addressed by integrating data analytics tools optimally and efficiently.
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Harsuminder Kaur Gill, Vivek Kumar Sehgal and Anil Kumar Verma
Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive…
Abstract
Purpose
Epidemics not only affect the public health but also are a threat to a nation's growth and economy as well. Early prediction of epidemic can be beneficial to take preventive measures and to reduce the impact of epidemic in an area.
Design/methodology/approach
A deep neural network (DNN) based context aware smart epidemic system has been proposed to prevent and monitor epidemic spread in a geographical area. Various neural networks (NNs) have been used: LSTM, RNN, BPNN to detect the level of disease, direction of spread of disease in a geographical area and marking the high-risk areas. Multiple DNNs collect and process various data points and these DNNs are decided based on type of data points. Output of one DNN is used by another DNN to reach to final prediction.
Findings
The experimental evaluation of the proposed framework achieved the accuracy of 87% for the synthetic dataset generated for Zika epidemic in Brazil in 2016.
Originality/value
The proposed framework is designed in a way that every data point is carefully processed and contributes to the final decision. These multiple DNNs will act as a single DNN for the end user.
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An Thi Binh Duong, Tho Pham, Huy Truong Quang, Thinh Gia Hoang, Scott McDonald, Thu-Hang Hoang and Hai Thanh Pham
The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.
Abstract
Purpose
The present study is performed to identify the propagation mechanism of the ripple effect as well as examine the simultaneous impact of risks on supply chain (SC) performance.
Design/methodology/approach
A theoretical framework with many hypotheses regarding the relationships between SC risk types and performance is established. The data are collected from a large-scale survey supported by a project of the Japanese government to promote sustainable socioeconomic development for the Association of Southeast Asian Nations (ASEAN) region, with the participation of 207 firms. Structural equation modeling (SEM) is used to test the hypotheses of the theoretical framework.
Findings
It is indicated that human-made risk causes operational risk, while natural risk causes both supply risk and operational risk. Furthermore, the impacts of human-made risk and natural risk on performance are amplified through operational risk.
Research limitations/implications
This study is one of the first attempts that identifies the propagation mechanism of the ripple effect and examines the simultaneous impact of risks on performance in construction SCs.
Originality/value
Although many studies on risk management in construction SCs have been carried out, they mainly focus on risk identification or quantification of risk impact. It is observed that research on the ripple effect of disruptions has been very scarce.
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Shahbaz Khan, Abid Haleem and Mohd Imran Khan
The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM)…
Abstract
Purpose
The complex network structure causes several disruptions in the supply chain that make risk management essential for supply chain management including halal supply chain (HSM). During risk management, several challenges are associated with the risk assessment phase, such as incomplete and uncertain information about the system. To cater this, the authors propose a risk assessment framework that addresses the issues of uncertainty using neutrosophic theory and demonstrated the applicability of the proposed framework through the case of halal supply chain management (HSCM).
Design/methodology/approach
The proposed framework is using the capabilities of the neutrosophic number which can handle uncertain, vague and incomplete information. Initially, the risk related to the HSC is identified through a literature review and expert’s input. Further, the probability and impact of each HSM-related risk are assessed using experts’ input through linguistic terms. These linguistic values are transformed into single-value trapezoidal neutrosophic numbers (SVTNNs). Finally, the severity of each HSM-related risk is determined through the multiplication of the probability and impact of each risk and prioritised the risks based on their severity.
Findings
A comprehensive risk assessment framework is developed that could be used under uncertainty. Initially, 16 risks are identified related to the HSM. Further, the identified risks are prioritised using the severity of the risks. The high-priority risk is “raw material status”, “raw material wholesomeness” and “origin of raw material” while “information integrity” and “people integrity” are low-priority risks.
Practical implications
HSM risk can be effectively assessed through the proposed framework. The proposed framework applied neutrosophic numbers to represent real-life situations, and it could be used for other supply chains as well.
Originality/value
The proposed method is effectively addressing the issue of linguistic subjectivity, inconsistent information and uncertainty in the expert’s opinion. A case study of the HSC is adopted to illustrate the efficiency and applicability of the proposed risk framework.
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Serkan Ayvaz and Salih Cemil Cetin
The purpose of this paper is to develop a model for autonomous cars to establish trusted parties by combining distributed ledgers and self-driving cars in the traffic to provide…
Abstract
Purpose
The purpose of this paper is to develop a model for autonomous cars to establish trusted parties by combining distributed ledgers and self-driving cars in the traffic to provide single version of the truth and thus build public trust.
Design/methodology/approach
The model, which the authors call Witness of Things, is based on keeping decision logs of autonomous vehicles in distributed ledgers through the use of vehicular networks and vehicle-to-vehicle/vehicle-to-infrastructure (or vice versa) communications. The model provides a single version of the truth and thus helps enable the autonomous vehicle industry, related organizations and governmental institutions to discover the true causes of road accidents and their consequences in investigations.
Findings
In this paper, the authors explored one of the potential effects of blockchain protocol on autonomous vehicles. The framework provides a solution for operating autonomous cars in an untrusted environment without needing a central authority. The model can also be generalized and applied to other intelligent unmanned systems.
Originality/value
This study proposes a blockchain protocol-based record-keeping model for autonomous cars to establish trusted parties in the traffic and protect single version of the truth.