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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Chia-Chen Chen, Carmen Cámara, Kuo-Lun Hsiao, Tien-Yu Hsu and Arun Kumar Sangaiah
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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Aditya Khamparia, Sagar Pande, Deepak Gupta, Ashish Khanna and Arun Kumar Sangaiah
The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).
Abstract
Purpose
The purpose of this paper is to propose a structured multilevel system that will distinguish the anomalies present in different online social networks (OSN).
Design/methodology/approach
Author first reviewed the related work, and then, the research model designed was explained. Furthermore, the details regarding Levels 1 and 2 were narrated.
Findings
By using the proposed technique, FScore obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.
Research limitations/implications
Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.
Originality/value
This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.
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Mamta Kayest and Sanjay Kumar Jain
Document retrieval has become a hot research topic over the past few years, and has been paid more attention in browsing and synthesizing information from different documents. The…
Abstract
Purpose
Document retrieval has become a hot research topic over the past few years, and has been paid more attention in browsing and synthesizing information from different documents. The purpose of this paper is to develop an effective document retrieval method, which focuses on reducing the time needed for the navigator to evoke the whole document based on contents, themes and concepts of documents.
Design/methodology/approach
This paper introduces an incremental learning approach for text categorization using Monarch Butterfly optimization–FireFly optimization based Neural Network (MB–FF based NN). Initially, the feature extraction is carried out on the pre-processed data using Term Frequency–Inverse Document Frequency (TF–IDF) and holoentropy to find the keywords of the document. Then, cluster-based indexing is performed using MB–FF algorithm, and finally, by matching process with the modified Bhattacharya distance measure, the document retrieval is done. In MB–FF based NN, the weights in the NN are chosen using MB–FF algorithm.
Findings
The effectiveness of the proposed MB–FF based NN is proven with an improved precision value of 0.8769, recall value of 0.7957, F-measure of 0.8143 and accuracy of 0.7815, respectively.
Originality/value
The experimental results show that the proposed MB–FF based NN is useful to companies, which have a large workforce across the country.
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Shreya Sangal, Achint Nigam and Chitrakshi Bhutani
This study aims to identify the challenges in the healthcare industry as it adopts an omnichannel setup in an emerging economy context. Further, the study determines the scope of…
Abstract
Purpose
This study aims to identify the challenges in the healthcare industry as it adopts an omnichannel setup in an emerging economy context. Further, the study determines the scope of blockchain in addressing these challenges.
Design/methodology/approach
The study uses a qualitative approach to understand the challenges in the omnichannel healthcare industry and know the scope of blockchain in building an omnichannel healthcare system. In the first stage, it did an in-depth analysis of the extant literature, followed by a Delphi study with 24 healthcare experts.
Findings
The study presents the current challenges in the omnichannel healthcare sector in an emerging economy. Further, it develops a novel conceptual framework for blockchain adoption in the omnichannel healthcare industry. The study also presents propositions that will help healthcare service providers enhance decision-making concerning the adoption of blockchain in the healthcare industry.
Research limitations/implications
The research results may lack generalizability due to the exploratory approach and emerging economies context. Theoretically, in this study, the authors extend the theory of swift trust and organization information processing theory in an omnichannel healthcare context.
Practical implications
The propositions provided in this paper can help healthcare managers make strategic decisions on the scope of adoption of blockchain for omnichannel healthcare.
Originality/value
This study explores the understudied area of challenges in omnichannel healthcare and the scope of blockchain for omnichannel healthcare in an emerging economy context.
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Arman Firoz Velani, Vaibhav S. Narwane and Bhaskar B. Gardas
This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and…
Abstract
Purpose
This paper aims to identify the role of internet of things (IoT) in water supply chain management and helps to understand its future path from the junction of computer science and resource management.
Design/methodology/approach
The current research was studied through bibliometric review and content analysis, and various contributors and linkages were found. Also, the possible directions and implications of the field were analyzed.
Findings
The paper’s key findings include the role of modern computer science in water resource management through sensor technology, big data analytics, IoT, machine learning and cloud computing. This, in turn, helps in understanding future implications of IoT resource management.
Research limitations/implications
A more extensive database can add up to more combinations of linkages and ideas about the future direction. The implications and understanding gained by the research can be used by governments and firms dealing with water management of smart cities. It can also help find ways for optimizing water resources using IoT and modern-day computer science.
Originality/value
This study is one of the very few investigations that highlighted IoT’s role in water supply management. Thus, this study helps to assess the scope and the trend of the case area.
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Fahimeh Aliakbari Nouri and Mohsen Shafiei Nikabadi
This study aims to identify the challenges faced by taxpayers in adopting electronic invoicing for value-added tax (VAT) collection and develop a framework for addressing these…
Abstract
Purpose
This study aims to identify the challenges faced by taxpayers in adopting electronic invoicing for value-added tax (VAT) collection and develop a framework for addressing these challenges based on their interrelationships within a developing country.
Design/methodology/approach
To establish a practical framework, a comprehensive literature review was conducted. The extracted factors were then presented to a panel of experts for validation or modification. Subsequently, this study employed a multi-criteria model based on DEMATEL and interval neutrosophic value set (INVS) to assist decision-makers in evaluating taxpayer challenges and identifying their interdependencies. This research adopts a mixed-methods approach, combining library research, expert interviews/consultations (qualitative) and a survey (quantitative).
Findings
The study suggests that taxpayer challenges can be categorized into six primary factors: distrust and security concerns, technical challenges, cost considerations, regulatory compliance challenges, cultural/demographic factors and lack of awareness. Key findings reveal that lack of awareness (X6) and cultural/demographic factors (X5) emerged as the most critical factors in terms of both importance and influence on other factors.
Practical implications
This study offers a more realistic understanding of cause-and-effect relationships, ultimately leading to more informed decision-making regarding e-invoicing adoption. The findings provide valuable insights for policymakers, guiding them towards effective practical implications.
Originality/value
This study differentiates itself from previous research by not only prioritizing factors influencing taxpayer e-invoicing adoption but also by examining the causal relationships between these factors. Unlike prior studies, this research has delved into the interdependencies among the prerequisite variables of e-invoicing adoption for VAT in a developing country. Moreover, to the best of our knowledge, no existing research has employed neutrosophic DEMATEL to address the uncertainty inherent in identifying the interrelationships among factors affecting e-invoicing adoption by taxpayers.