Fuzzy Analytic Hierarchy Process Analysis Research Articles

Enhancing Student Performance through Fuzzy MCDM: Evaluating Family Concern, Study Environment, and other Key Factors

Abstract: In this study, the Fuzzy Analytic Hierarchy Process (FAHP) was utilized to evaluate factors affecting student wellbeing and performance. The criteria assessed included C1 - Family Concern, C2 - Environment of Study, C3 - Resources, C4 - Time Management, and C5 - Lecturer Concern. A survey was administered to students at United College of Arts and Science in Coimbatore, Tamil Nadu, India, to gather numerical data. Pairwise comparison matrices were created based on the survey responses to assess the relative importance of each criterion. The FAHP analysis revealed that Family Concern (C1) has the greatest impact on student outcomes, highlighting the crucial role of family support in student success and well-being. The findings suggest that educators and parents should prioritize addressing family-related issues and consider implementing additional supportive measures, such as yoga and sports activities, to further improve student performance and overall wellbeing

Topological network and fuzzy AHP modeling framework for the suitability analysis of evacuation shelters: A case study in Japan

Evacuation shelters play a critical role in disasters, providing a safe environment for evacuees to remain safe from threats or disasters. In this study, we analyze the suitability of evacuation shelters using a topological network and fuzzy analytic hierarchy process (AHP) modeling framework with GIS applications, in which potential shelters are assessed according to their accessibility, reachability, and critical criteria within an evacuation network. The accessibility and reachability of evacuation shelters are identified using network analysis, whereas the critical criteria for evacuation shelters are deduced from the referenced requirements. The accessibility, reachability, and criteria of shelters are then weighted with fuzzy AHP analysis, and the suitability of potential shelters for use as evacuation shelters are then analyzed. An illustrative case study was conducted to illustrate the modeling framework; an evacuation network with 2797 nodes was constructed in the study area. Of the 2797 nodes, nine were identified as suitable for use as evacuation shelters. These nine included four accredited designated evacuation shelters and another five potential shelters as alternative shelters. The modeling framework in this study provides a systematic approach to identifying the characteristics of potential shelters, which is expected to be useful in decision making for evacuation planning, disaster preparedness and response, and postdisaster activities in recovery and restoration.

Exploring and evaluating the development of an open application programming interface (Open API) architecture for the fintech services ecosystem

PurposeThe Open API (application programming interface) architecture will play an important role in promoting future FinTech service applications; however, it involves user data, and the current specialization and progression are less visible. Therefore, an evaluation framework for Open API development in the FinTech service ecosystem is constructed in this study.Design/methodology/approachThis study preliminarily selects the four most important key objects and factors of this ecosystem and conducts expert interviews to revise the evaluation framework. Then, this study uses the fuzzy analytic hierarchy process (FAHP) to evaluate the objects and their factor weights and finally uses the FAHP analysis results to further apply the evaluation based on distance from average solution (EDAS) approach to explore the strategy optimization scenarios.FindingsAccording to the analysis results, the co-creation object and productivity object are the two most significant objects, with weights of 0.275 and 0.272, respectively. The analysis shows that FinTech-related companies expect to increase productivity through co-creation. Finally, the results also indicate that mobile payment is the best Open API application scenario in the FinTech service ecosystem, followed by online banking. These results illustrate strategic and management implications.Originality/valueThis study screens key evaluation criteria with a literature review and expert questionnaire interviews to process quantitative research. It can determine the weights of objectives and criteria to clarify the strength of influence between the objectives and criteria. Next, this study measures the probable performance of Open API applied in various FinTech service ecosystem scenarios.

Unraveling the influence of green bonds on environmental sustainability and paving the way for sustainable energy projects in green finance.

The acceleration of renewable energy has emerged as a cornerstone strategy in mitigating climate change and advancing the sustainable stewardship of our natural resources. Nonetheless, financing renewable energy projects remains a challenging issue. In this context, green bonds have surfaced as a promising financial instrument to propel renewable energy projects forward and foster sustainable resource development. This study endeavors to evaluate the transformative impact of green bonds on renewable energy investments in China. Leveraging the fuzzy analytical hierarchy process (AHP) and the fuzzy weighted aggregates sum product assessment (WASPAS) methods, we delve into the Chinese landscape to dissect the correlation between green bonds and renewable energy investment outcomes. Through extensive literature review, we have identified several factors, comprising nuanced sub-factors, alongside distinctive investment strategies pertinent to the effective utilization of green bonds in the renewable energy sector. The fuzzy AHP analysis reveals that financial, environmental, and regulatory are the most influential factors. Employing the fuzzy WASPAS method, our findings emphasize the transformative potential of green bonds in significantly accessing to capital of renewable energy projects in the context of Chinese. This research sheds light on the pivotal role green bonds play in driving sustainable natural resource development through substantial investments in renewable energy projects.

Operational Barriers against the Use of Smart Contracts in Construction Projects

As an emerging but embryonic way of contract administration, smart contracts can play a prominent role in managing construction projects in an effective manner. However, there are still some barriers preventing the implementation of them in the life cycles of construction projects. This study investigates operational barriers against the adoption of smart contracts in construction projects and explores the challenges in this process. Operational barriers against smart contract implementation are identified through a comprehensive literature review and a focus group discussion is performed to refine the identified barriers. These barriers are evaluated through fuzzy analytical hierarchy process analysis. Finally, a framework is proposed for the adoption of smart contracts effectively in construction projects. 20 operational barriers were attained based on four main barrier categories: technical, financial, security/technological, and time. The results show that financial and technical aspects establish the most significant categories hindering the adoption of smart contracts, while expensive and clunky drafting and registration process, and cost of upskilling are the most significant barriers. Overall, the proposed framework might be useful for practitioners and project managers, who decide to use smart contracts in managing construction projects. The motive behind understanding critical operational barriers is to assist construction practitioners in automating contract execution processes. This study provides a basis for recommending the necessary strategies for the use of smart contracts in the industry to researchers in the construction management field.

Evaluating the impact of green bonds on renewable energy investment to promote sustainable development in China

The rapid development of renewable energy (RE) has become a crucial strategy to mitigate climate change and promote sustainable development. However, financing RE projects is often challenging due to high upfront costs, complex regulatory frameworks, and lack of access to capital. Green bonds have emerged as a promising tool for financing RE projects and promoting sustainable development. This study evaluates the impact of green bonds on RE investment in China using a fuzzy analytical hierarchy process (FAHP) and a fuzzy weighted aggregates sum product assessment (WASPAS) method. The study identifies six factors, 18 sub-factors, and six investment strategies through extensive literature works. The FAHP method is used to evaluate various factors and sub-factors, while the fuzzy weighted aggregates sum product assessment (FWASPAS) method is employed to identify the key strategies for green bonds implementation in RE projects. The FAHP analysis finds that the financial impact of green bonds is the most significant factor with financial feasibility and cost of capital being the most important sub-factors in this category. The environmental, regulatory, and market are the most important sub-factors. The FWASPAS method indicates that green bonds can have significant impact on lowering the cost of capital, improving investor confidence, and supporting project certification of RE projects.

Assessing environmental, social, and governance performance and natural resource management policies in China's dual carbon era for a green economy

As the globe faces urgent environmental concerns and the need to move toward a greener and more sustainable economy, the idea of sustainability has received a lot of attention recently. Evaluation of the environmental, social, and governance (ESG) performance and natural resource management (NRM) policy options are crucial given the urgent environmental issues the world is facing and the requirement for sustainable development. The objective of this study is to assess China's ESG performance and NRM policy options in the dual carbon era for developing green economy. The dual carbon places a focus on the need of lessening carbon emissions and encouraging low-carbon activities and technologies. A hybrid multi-criteria decision making (MCDM) methods i.e. Fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)-GREY are used to evaluate and prioritize the criteria, sub-criteria, and alternatives. The FAHP method is used to assess the criteria and sub-criteria of ESG performance. Moreover, the TOPSIS-Grey method is employed to prioritize the NRM policy options. The findings of FAHP analysis reveal that environment is the most crucial criteria, followed by governance and social performance. While the TOPSIS-Grey analysis show that green finance and investment, policy and regulatory reforms, and circular economy practices are the most suitable NRM policy options. China can significantly advance toward a more ecologically and socially responsible future while fostering economic growth and prosperity in the dual carbon era by implementing the recommended sustainable practices and policies.

Gap Analysis Between the Level of Heat Wave Adaptation Policy and Heat Wave Effects in South Korean Municipalities

<p>This study aims to analyze the gap between the level of heat wave adaptation policies and heat wave effects in South Korean municipalities. First, the types of industries in municipalities were classified using factor analysis and cluster analysis. Second, the level of heat wave adaptation policy in the municipalities was assessed using a fuzzy analytic hierarchy process analysis. Third, the gap between the level of heat wave adaptation policy and the heat wave effect was analyzed. The results show that the heat wave adaptation policies were established in accordance with the heat wave effects to at least some degree. However, closer to the long-term future (2095), the policies have not sufficiently matched the level of heat wave effects. The proportion of municipalities with insufficient levels of heat wave adaptation policies against the heat wave effects was higher among urban-type municipalities. The analysis results suggest two policy implications. First, the heat wave adaptation policies of municipalities should be established through continuous feedback on the predictions of future heat wave effects. Second, urban-type municipalities should strengthen their planning authority and competence by securing a professional workforce and budgets for the establishment of heat wave adaptation policies.<strong></strong></p>

Fuzzy AHP approach to evaluate incentive factors of high-tech talent agglomeration

To compete with the speedy revolution of high technological innovation and restarted economy for the post-COVID-19 period in China, governments and organizations should be active in attracting high-tech talent to enhance independent and indigenous R&D capability. Talent agglomeration effectiveness is the strongest endogenous force pushing competitiveness for regional economy and industrial development. Due to the complexity of high-tech talent agglomeration, there are still considerable gaps to evaluate the incentive factors. This study evaluates the influential indicator system by using a hybrid fuzzy set theory extended Analytic Hierarchy Process (AHP) approach for proximity to reality from individual, organizational and environmental dimensions. The statistical analysis is adopted to verify the results of fuzzy AHP analysis. This research explores the founding that individual incentives are more important than environmental factors, and environmental incentives are more influential than organizational incentives. Job satisfaction, welfare system, and geographical location are the highest ranking factors. High-tech start-ups should give priority to combine geographical location with political support to reserve site selection or firm relocation for a great effectiveness of high-tech talent agglomeration.

Prioritization of Contracting Methods for Water and Wastewater Projects Using the Fuzzy Analytic Hierarchy Process Method

This study uses the fuzzy analytical hierarchy process (FAHP) method to prioritize contracting methods to determine the most suitable contract option for water and wastewater projects (WWP). Content analysis, a two-round Delphi survey technique, and a series of validation and reliability tests helped establish the 18 key criteria for FAHP analysis. Consequently, data collected from experts through a pairwise comparison questionnaire form the basis for the inputs for the FAHP analysis. Consequently, the final weightings were derived for each of the key criteria and available contracting methods. The results indicate that the bilateral, cooperative, and trilateral contracting methods are the most suitable for WWP in Iran, with the highest weighting. The study provides useful guidance for the top management of project firms in selecting the optimal contracting method for their projects and offers significant contributions from theoretical and practical perspectives.

The Integration of Fuzzy-ISM, Fuzzy-AHP, and Fuzzy-MICMAC Approach under Trapezoid Fuzzy Linguistic to Analyze Enablers of The Logistics Outsourcing Relationship: Mekong Delta, Vietnam Rice Supply Chain Context

The purpose of this paper is to analyze the effects of the factors and determine the importance of these factors to the LO relationship with the desire to improve the efficiency in logistics activities of the supply chain. An integrated approach including Fuzzy Interpretation Structure Model (FISM), Fuzzy Cross-Impact Matrix Multiplication Applied to Classification (FMICMAC) analysis, Fuzzy Analytic Hierarchy Process (FAHP) is structured in reaching this purpose. Specifically, the impact of factors on the LO relationship will be determined through the FISM-FMICMAC method, then FAHP will use the results from this FISM-FMICMAC analysis step to perform the determination of the level of importance of contributing factors to the LO relationship. The fuzzy number formats of this paper are all in trapezoidal format. To evaluate the proposed framework, a typical example of logistics activity in the Mekong Delta Rice Supply Chain (SuC) was selected. The results have shown the impact level of 14 factors on the LO relationship under 4 clusters (Dependent, Linkage, Independent Autonomous). Finally, only the 10 most outstanding of the 14 factors were used to conduct FAHP analysis to find the global weightages which contribute to the LO relationship by each factor.

Fuzzy Multi-Criteria Decision-Making Approach for Online Food Delivery (OFD) Companies Evaluation and Selection: A Case Study in Vietnam

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.

Evaluating Decision Making in Sustainable Project Selection Between Literature and Practice

A robust project selection process is critical for the selection of sustainable projects that meet the needs of an organization or community. There are multiple factors or criteria that can be considered in the selection of the appropriate sustainable project, but it can be challenging to find sufficient depth of expert opinion to perform a strong evaluation of these criteria. Several researchers have turned to the sustainable project literature as a source of expert opinion to evaluate the criteria used in sustainable project selection and rank them based on importance using different multi-criteria decision-making (MCDM) methodologies. However, using the literature as a source of expert opinion poses a different set of challenges and may not accurately represent the actual opinions of sustainable project subject matter experts (SMEs) and practitioners. In this study, the fuzzy analytic hierarchy process (FAHP) methodology is used to determine the importance of project cost, project maturity, skill and experience, uncertainty, and technology information transfer as selection criteria using collected opinions from academic sustainable project experts and practitioners. The results are then compared with previous research that used the literature to rank these five criteria based on importance when selecting between multiple sustainable project alternatives. The results show that project cost is still considered the major driver of decision making in sustainable project selection by both the literature and practice. However, unlike the literature-as-experts approach, SMEs prioritize skill and experience and technology information transfer over project maturity and uncertainty. Project managers and decision makers can use these findings to best prioritize the types of challenges that may occur depending on inputs for the FAHP analysis.

Morphometric analysis using fuzzy analytical hierarchy process (FAHP) and geographic information systems (GIS) for the prioritization of watersheds

River basins are prone to degradation due to soil erosion induced by anthropogenic activities and natural calamities. In this study, an integrated approach using morphometric analysis, geo-informatics, and fuzzy analytical hierarchy process was employed to prioritize the watersheds. Hydrological parameter “erosion” is a major deciding factor to assess and prioritize the watersheds using the fuzzy analytical hierarchy process (FAHP) method in the Peddavagu watershed of the Krishna river basin. The major characteristics of watershed parameters such as basin length (Lb), drainage density (Dd), form factor, stream frequency (Fs), elongation ratio (Re), circularity ratio (Rc), drainage texture (T), bifurcation ratio (Rb), and compactness constant (Cc) are arranged in matrix form for FAHP analysis. The FAHP analysis was carried out using Triangular Fuzzy Network; for further analysis, the values were classified as follows: 1.25 as moderate susceptibility, 1.5 as high susceptibility, and 1.75 as very high susceptibility. The results of FAHP analysis showed that five watersheds have a very high susceptibility to erosion (30.32%), 16 watersheds as high susceptibility (53.28%), and the remaining 10 watersheds were categorized as moderate susceptibility (16.4%). It implies that soil and water conservation measures have to be implemented on priority in “very high susceptibility category watersheds,” followed by the “high susceptibility” and “moderate susceptibility” categories. Furthermore, the universal soil loss equation (USLE) equation was used to compare the outcomes of the FAHP method. The results have been complacent with FAHP analysis, and the very high susceptibility, high susceptibility, and moderate susceptibility categories were having sediment yields of 54.96 t/ha/year (4D2D1-26), 30.00 t/ha/year (4D2D3-31), and 15.07 t/ha/year (4D2D2-17). The Spearman rank correlation coefficient has been used to validate the USLE and Fuzzy simulations. The results have shown a strong positive correlation for the study area. As the integrated morphometric analysis using FAHP for prioritizing watersheds has shown reliable outcomes, this method has the potential for adoption in other case studies elsewhere.

Evaluating Industry 4.0 Implementation Challenges Using Interpretive Structural Modeling and Fuzzy Analytic Hierarchy Process

The fourth industrial revolution known as Industry 4.0 is reshaping and evolving the way industries produce products and individuals live and work therefore, gaining massive attraction from academia, business, and politics. The manufacturing industries are optimistic regarding the opportunities that Industry 4.0 may offer such as improved efficiency, productivity and customization. The present research contributes to the Industry 4.0 literature by identifying, modeling, analyzing, and prioritizing the challenges in implementing Industry 4.0 in manufacturing industries. In doing so, the article first introduces the interpretive structural modeling (ISM) to develop the hierarchical relationships among the challenges and analyzes their mutual interactions. Further, “Matrice d’Impacts Croises Multiplication Appliquee aun Classement” (MICMAC) analysis is used to categorize the challenges into four categories, namely autonomous, driver, dependent, and linkage based on their driving power and dependence power. Moreover, fuzzy analytic hierarchy process (F-AHP) methodology is used to prioritize the challenges based on three criteria: driving power, dependence power, and change management. The hierarchical model developed through ISM methodology shows that “lack of vision and leadership from top management (C12), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are the major challenges in implementing Industry 4.0 in manufacturing industries. The findings of F-AHP analysis suggest that “lack of vision and leadership from top management (C12), lack of skilled workforce (C3), lack of skills training program and education (C2), and uncertainty of return on investment (C9)” are some of the major challenges of implementing Industry 4.0. Finally, the obtained results show how challenges affect other so that to uncover the root cause triggering the other challenges. The industrial practitioners and managers can then take advantage of these analyses to know which challenge acts as the main barrier in implementing Industry 4.0 and to be focused first in order to reach a solution.

Comparison of Fuzzy AHP and AHP in Multicriteria Inventory Classification While Planning Green Infrastructure for Resilient Stream Ecosystems

As climate change-induced weather variability increases, various green infrastructure plans, such as stream ecosystems, have been studied to overcome ecological and environmental problems arising from extreme weather events; however, our understanding of them and their resilience to extreme weather events is considerably limited. This study proposes a multicriteria inventory classification while planning green infrastructure for resilient stream ecosystems under extreme weather events. Literature reviews, expert surveys, and reliability/validity analyses were used to enlist indicators for this classification. The analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (fuzzy AHP) were used to compute the weights and ranks of indicators for identifying critical indices while planning green infrastructure. The AHP and fuzzy AHP analysis suggested that meteorological phenomena and disasters, hydraulic characteristic of streams, land use/geographic characteristics, and experience/damage restoration were important factors. High weights were attributed to aquatic ecology, potentially vulnerable areas, population, topography, and heat waves. The weights and ranks attributed by AHP and fuzzy AHP varied slightly, but the indicator groups with high and low weights were the same; hence, primary indicators to be considered while planning green infrastructure for resilient stream ecosystems could be suggested. These results could be used as a preliminary analysis in establishing countermeasures against climate change or in distributing budgets for green infrastructure plans.

Assessing and Prioritizing the Climate Change Policy Objectives for Sustainable Development in Pakistan

The world is facing the observable and direct impacts of climate change in the shape of extreme weather events, irregular precipitation, glacial melt, sea-level rise, an asymmetric average temperature trends, higher oceanic temperatures, damage to natural ecosystems, and biodiversity. In 2015, collective wisdom stirred the global community to agree upon two unprecedented milestones in recent human history—the Paris agreement and sustainable development goals (SDGs). The twin global agreements set a platform for collective efforts to secure socio-economic and climatic sustainability. Pakistan also joined the board to put forth policy interventions for the mitigation and adaption of climate change risks to maintain symmetry between the environmental quality and economic development. The government of Pakistan (GOP) formulated the National Climate Change Policy (NCCP (2012)) and passed the Pakistan Climate Change Act (PCCA (2017)) to provide an impetus for the implementation of the NCCP. Yet, an appropriate assessment and prioritization of the objectives of the NCCP are indispensable for productive and effective policies to achieve the targets. This study serves this purpose by prioritizing the climate change policy objectives (CCPOs) based on symmetric principles, i.e., energy, transport, urban and town planning, industry, and agriculture as criteria, with 17 sub-criteria in total. The fuzzy analytical hierarchy process (AHP) results show that the energy sector is the most pivotal while implementing the NCCP. Energy production is the most critical area that needs mitigation policy intervention for shifting the energy mix of the economy from high-carbon to low-carbon energy. The fuzzy AHP analysis further revealed the railway, population and urbanization, air pollution, crop growing practices and techniques as the most important related to transport, urban planning, industry, and agriculture sub-criteria, respectively. The fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis showed the ranking of the CCPOs from high to low through the integration of policies, institutional capacity building, water security, natural resource management, natural disaster management, environmental financial structure development, and social sector development. The findings of the present research would be helpful for experts and policymakers to re-examine the NCCP and put forth action plans to achieve sustainable climate and SDGs.

Analyzing Renewable Energy Sources of a Developing Country for Sustainable Development: An Integrated Fuzzy Based-Decision Methodology

Global human pollutant activities have raised greenhouse gas (GHG) emissions, which have directly affected the climate. Fossil fuel-based energy has brought a negative impact on the environment and is considered one of the largest sources of GHG emissions. It is envisaged that GHG emissions will increase in the future due to rapid population growth and industrialization. Thus, it is imperative to mitigate climate variability and reduce GHGs by adopting renewable energy (RE) sources for electricity generation. In this regard, the multi-criteria decision analysis (MCDA) process would serve the purpose of framing out energy policy to analyze these environmentally friendly energy sources. This study uses an integrated decision methodology—a combination of Delphi, fuzzy analytical hierarchy process (FAHP), and the fuzzy weighted aggregated sum product assessment (FWASPAS)—for the adoption of RE sources for electricity generation in Turkey. Initially, the study identified five main criteria and seventeen sub-criteria using the Delphi method. Then, the FAHP method was used to evaluate and rank the main criteria and sub-criteria. Finally, the FWASPAS method was used to assess and prioritize five major RE sources for electricity generation. The FAHP analysis indicated that political criteria are the most influential, followed by economic and technical criteria. Further, the FWASPAS method revealed that wind energy is the most significant option for electricity generation. This decision-making process can help the energy planners to utilize RE sources for sustainable development.

RETRACTED ARTICLE: Identification and prioritization of DevOps success factors using fuzzy-AHP approach

DevOps (development and operations) is a collaborative and multidisciplinary organizational effort to automate continuous delivery of a software project with an aim to improve software quality. The implementation of DevOps practices is not straightforward as there are several complexities associated with it. The aim of this study is to identify and prioritize the factors that positively influence the DevOps practices in software organizations. Using a systematic literature review, 19 factors were identified. The identified factors were further validated with experts via a questionnaire survey study. Finally, Fuzzy Analytical Hierarchy Process (FAHP) was used to prioritize the identified success factors. The results indicate that “DevOps security pipeline,” “use system orchestration” and “attempt matrix organization and transparency” factors are the highest ranked success factors for the successful implementation of DevOps practices. The FAHP analysis is novel in this research area as it provides the prioritization based taxonomy of the identified factors which will assist the researchers and practitioners to focus on the critical areas that are significant for the successful adoption of DevOps practices.

Quantifying SWOT analysis for cloud adoption using FAHP-DEMATEL approach: evidence from the manufacturing sector

PurposeThis study aims to identify the critical factors (barriers and drivers) influencing the adoption of cloud computing (ACC) in the manufacturing sector in India.Design/methodology/approachIn this study, a mixed methodology approach is used. Interviews are conducted to investigate factors (drivers and barriers) influencing the ACC, which are further categorized as controllable determinants (weaknesses and strengths) and uncontrollable determinants (threats and opportunities) using a SWOT analysis. Fuzzy analytic hierarchy process (FAHP) has been utilized to highlight the most critical drivers as well as barriers. Finally, decision-making trial and evaluation laboratory (DEMATEL) has been used to find the cause-effect relationships among factors and their influence on the decision of adoption.FindingsThe manufacturing sector is in the digital and value change transformation phase with Industry 4.0, that is, the next industrial revolution. The 24 critical factors influencing ACC are subdivided into strengths, weaknesses, opportunities and threats. The FAHP analysis ranked time to market, competitive advantage, business agility, data confidentiality and lack of government policy standards as the most critical factors. The cause-effect relationships highlight that time to market is the most significant causal factor, and resistance to technology is the least significant effect factor. The results of the study elucidate that the strengths of ACC are appreciably more than its weaknesses.Research limitations/implicationsThis study couples the technology acceptance model (TAM) with technology-organization-environment (TOE) framework and adds an economic perspective to examine the significant influences of ACC in the Indian manufacturing sector. Further, it contributes to the knowledge of ACC in general and provides valuable insights into interrelationships among factors influencing the decision and strategies of adoption in particular.Originality/valueThis is the first scholarly work in the Indian manufacturing sector that uses the analysis from SWOT and FAHP approach as a base for identifying cause-effect relationships between the critical factors influencing ACC. Further, based on the extant literature and analysis of this work, an adoption framework has been proposed that justifies that ACC is not just a technological challenge but is also an environmental, economic and organizational challenge that includes organizational issues, costs and need for adequate government policies.