Modeling the Big Data challenges in context of smart cities – an integrated fuzzy ISM-DEMATEL approach

Khan, Mohd Imran; Khan, Shahbaz; Khan, Urfi; Haleem, Abid

doi:10.1108/ijbpa-02-2021-0027

Cited by 38 publications

(19 citation statements)

References 122 publications

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Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

“…• It was the goal of the work by [10], [9] to identify and analyze the interrelationships between the issues associated with effectively implementing Big Data in smart city development. To identify and validate the 14 Big Data problems, [10] conducted a literature review. Fuzzy Interpretive Structural Modeling (fuzzy-ISM) (Figure 8) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DMTL) are used to develop the inter-relationships between the highlighted issues (fuzzy-DEMATEL).…”

Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

“…Fuzzy Interpretive Structural Modeling (fuzzy-ISM) (Figure 8) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DMTL) are used to develop the inter-relationships between the highlighted issues (fuzzy-DEMATEL). Big Data integration in smart cities is hindered by a diverse population and a lack of infrastructure, according to the [10] study's conclusions. According to [10] • Both [14], [19] studies concentrated on the developing countries.…”

Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

“…The full potential of smart cities using Big Data requires overcoming a number of obstacles, including the availability of Big Data analytics tools, the accuracy and representation of real-time analytics, privacy concerns, and reliable infrastructure [10]. Big Data security shares numerous characteristics with traditional information system security (where data are structured).…”

Section: Introductionmentioning

confidence: 99%

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Challenges and Obstacles Facing Data in the Big Data Environment

Aloufi¹,

Abdulaziz

2022

Comm. Math. Appl.

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Big data is dubbed "today's digital oil" and the "new raw resource of the twenty-first century". BD is synonymous with the future of innovation, competition, and productivity. It can produce and find corporate value by analyzing data in ways that older methodologies could not. Regardless of its benefits, the development of big data continues to encounter various barriers, the most important of which are security and privacy concerns. As a result, this study is motivated by the need to address and evaluate big data challenges. Thus, by comparing and contrasting big data difficulties with available and potential solutions, users, developers, and businesses can find pertinent and timely responses to specific dangers, resulting in the best possible big data-based services. The objective of this essay is to highlight the inherent challenges of big data and some essential strategies for overcoming them.The purpose of this article was to extract and analyze significant works in order to contribute to the corpus of literature by emphasizing many critical difficulties in the big data domain and throwing light on how these challenges affect a range of domains, including users, sites, and business. Many issues such as data privacy, information sharing, failures in big data technologies and infrastructure, poor data quality management, managers and policymakers' inability to learn and adapt, the absence of government policies and plans, the lack of successfully implemented big data analytics projects, and the lack of human experience are among the most frequently mentioned issues. Obstacles also exist in the areas of real-time data collection, as well as real-time data processing and visualization, among others.By combining previously identified solutions, this research addressed these concerns. The consequences for both researchers and practitioners have been discussed. Aiming to help scholars gain a comprehensive understanding of these issues and confirm the approaches used to address them, this study's theoretical focus is broad. This study uses tried-and-true solutions to overcome these obstacles. Business and individuals using big data analytics systems will benefit from these solutions.

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Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

Section: The Details Of the Reviewed Articlesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Challenges and Obstacles Facing Data in the Big Data Environment

Aloufi¹,

Abdulaziz

2022

Comm. Math. Appl.

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“…After finalising the barriers, we have formed the SSIM matrix by using the experts' inputs as described in the methodology section. Like previous studies (e.g., Khan & Haleem, 2012;Khan et al, 2021;Sushil, 2017), four symbols (V, A, X, O) are used to denote the direction of the relationship between the barriers i and j. Table 3 shows the inputs of experts along with symbols in making the SSIM.…”

Section: Structural Self-interaction Matrix (Ssim)mentioning

confidence: 99%

Modelling of Barriers Towards the Adoption of Strategic Entrepreneurship: An Indian Context

Khan

Fatma

Khan

et al. 2021

Contextual Strategic Entrepreneurship

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The last three decades have seen focussed research on entrepreneurship and related strategic entrepreneurship. Organisations try to achieve global competitiveness by adopting strategic entrepreneurship. Despite having extensive benefits, we find that strategic entrepreneurship in developing countries is academically understudied. Further, due to several barriers, its adoption in practice is limited. This chapter primarily aims to identify the significant barriers towards adopting strategic entrepreneurship for the strategic management of entrepreneurial organisations. Thus, through expert inputs, twelve barriers were modelled through Interpretive Structural Modelling (ISM). ISM models the interrelationship among the identified barriers so that the organisation can mitigate these barriers effectively. The most significant barriers revealed by the study were 'strategic entrepreneurship awareness', 'lack of entrepreneurship culture' and 'limited financial support to knowledge-based firms'.Further, in the next step, MICMAC analysis is applied to assess the identified barrier's driving and dependence power. These barriers are clustered into four categories, based on the driving/dependence power, namely autonomous, dependent, linkage and driver clusters. The finding of this study suggests that 'strategic entrepreneurship awareness', 'lack of entrepreneurship culture' and 'limited financial support to knowledge-based firms' are the most significant barriers towards the successful adoption of strategic entrepreneurship. Therefore, management needs to provide greater attention to the mentioned barriers to adopt a strategic perspective towards entrepreneurship.

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Green, resilient, agile, and sustainable fresh food supply chain enablers: evidence from India

2023

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The existing research on fresh food supply chains (FFSC) sustainability consisting of fur fundamental pillars, namely green (G), resilient (R), agile (A), and sustainability (S) (hereafter GRAS), is explored sparsely and needs thorough investigation. Further, conceptualization and mutual interactions among GRAS enablers that can help perpetuate sustainable supply chains (SSC) still need to be addressed. This study proposes a methodological framework to evaluate the SCS from the perspective of GRAS enablers with an application for the Indian FFSC. A mixed-method sequential approach was used with interviews followed by integrated fuzzy interpretive structural modelling—decision-making trial and evaluation laboratory (FISM-DEMATEL) techniques. The study recognizes twenty supply chain sustainability (SCS) enablers through an extensive literature review and discussions with the expert group. The research discloses that the firms' ‘organization culture’ acts as the most powerful driver in achieving sustainability in FFSC, followed by the firms’ ‘environmental certification program’ and ‘financial strength.’ This investigation helps the managers/policymakers of the Indian FFSC to ascertain and comprehend the most significant SCS enablers to achieve sustainability in the supply chain (SC). The causation of SCS enablers supports the managers in systematically focusing on the most significant enablers and working towards their successful implementation. According to our knowledge, this is the first scholarly work that establishes hierarchies and interrelationships among GRAS enablers, thereby providing a holistic picture to decision-makers while adapting such practices. Supplementary Information The online version contains supplementary material available at 10.1007/s10479-023-05176-x.

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Modeling the Big Data challenges in context of smart cities – an integrated fuzzy ISM-DEMATEL approach

Cited by 38 publications

References 122 publications

Challenges and Obstacles Facing Data in the Big Data Environment

Challenges and Obstacles Facing Data in the Big Data Environment

Modelling of Barriers Towards the Adoption of Strategic Entrepreneurship: An Indian Context

Green, resilient, agile, and sustainable fresh food supply chain enablers: evidence from India

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