Software as a service based CRM providers in the cloud computing: Challenges and technical issues

Souri, Alireza; Asghari, Parvaneh; Rezaei, Reza

doi:10.1007/s12927-017-0011-5

Cited by 34 publications

(16 citation statements)

References 29 publications

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“…Therefore, predicting consumer behavior could be of crucial importance for future business planning. An e-commerce company with the capability of anticipating consumers’ shopping behavior will gain several advantages such as increasing consumer purchase rates, increasing sales and consumer satisfaction, and greater competition (Souri et al 2017 ).…”

Section: Methodsmentioning

confidence: 99%

A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

Safara

2020

Comput Econ

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The knowledge-based economy has drawn increasing attention recently, particularly in online shopping applications where all the transactions and consumer opinions are logged. Machine learning methods could be used to extract implicit knowledge from the logs. Industries and businesses use the knowledge to better understand the consumer behavior, and opportunities and threats correspondingly. The outbreak of coronavirus (COVID-19) pandemic has a great impact on the different aspects of our daily life, in particular, on our shopping behaviour. To predict electronic consumer behaviour could be of valuable help for managers in government, supply chain and retail industry. Although, before coronavirus pandemic we have experienced online shopping, during the disease the number of online shopping increased dramatically. Due to high speed transmission of COVID-19, we have to observe personal and social health issues such as social distancing and staying at home. These issues have direct effect on consumer behaviour in online shopping. In this paper, a prediction model is proposed to anticipate the consumers behaviour using machine learning methods. Five individual classifiers, and their ensembles with Bagging and Boosting are examined on the dataset collected from an online shopping site. The results indicate the model constructed using decision tree ensembles with Bagging achieved the best prediction of consumer behavior with the accuracy of 95.3%. In addition, correlation analysis is performed to determine the most important features influencing the volume of online purchase during coronavirus pandemic.

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Section: Methodsmentioning

confidence: 99%

A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

Safara

2020

Comput Econ

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Section: Iot Applicationsmentioning

confidence: 99%

“…Figure 3 represents a complete taxonomy of IoT in the significant fields of application. The principal areas of application are focused on health care, the environment, smart cities, commercial, industrial, and infrastructural fields [85,86]. The applications and use of IoT in the different domains are what drive and explain the development of this new trend, leading to the acceptance of IoT by the new world [87].…”

Section: Iot Applicationsmentioning

confidence: 99%

Internet of Things and Its Applications: A Comprehensive Survey

et al. 2020

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With the evolution of the fifth-generation (5G) wireless network, the Internet of Things (IoT) has become a revolutionary technique that enables a diverse number of features and applications. It can able a diverse amount of devices to be connected in order to create a single communication architecture. As it has significantly expanded in recent years, it is fundamental to study this trending technology in detail and take a close look at its applications in the different domains. It represents an enabler of new communication possibilities between people and things. The main asset of this concept is its significant influence through the creation of a new world dimension. The key features required for employing a large-scale IoT are low-cost sensors, high-speed and error-tolerant data communications, smart computations, and numerous applications. This research work is presented in four main sections, including a general overview of IoT technology, a summary of previous correlated surveys, a review regarding the main IoT applications, and a section on the challenges of IoT. The purpose of this study is to fully cover the applications of IoT, including healthcare, environmental, commercial, industrial, smart cities, and infrastructural applications. This work explains the concept of IoT and defines and summarizes its main technologies and uses, offering a next-generation protocol as a solution to the challenges. IoT challenges were investigated to enhance research and development in the fields. The contribution and weaknesses of each research work cited are covered, highlighting eventual possible research questions and open matters for IoT applications to ensure a full analysis coverage of the discussed papers.

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“…A huge amount of resources are available, but all these resources could not be utilized efficiently as even the distributed computing could not use it as efficiently as it should be used . Cloud service providers are classified into three layers including software as a service (SaaS), infrastructure as a service (IaaS), and platform as a service (PaaS) . IaaS suggests virtualized resources such as storage on demand.…”

Section: Introductionmentioning

confidence: 99%

Task scheduling mechanisms in cloud computing: A systematic review

Motlagh

Movaghar

Rahmani

2019

Int J Communication

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Summary Today, cloud computing has developed as one of the important emergent technologies in communication and Internet. It offers on demand, pay per use access to infrastructure, platforms, and applications. Due to the increase in its popularity, the huge number of requests need to be handled in an efficient manner. Task scheduling as one of the challenges in the cloud computing supports the requests for assigning a particular resource so as to perform effectively. In the resource management, task scheduling is performed where there is the dependency between tasks. Many approaches and case studies have been developed for the scheduling of these tasks. Up to now, a systematic literature review (SLR) has not been presented to discover and evaluate the task scheduling approaches in the cloud computing environment. To overcome, this paper presents an SLR‐based analysis on the task scheduling approaches that classify into (a) single cloud environments that evaluate cost‐aware, energy‐aware, multi‐objective, and QoS‐aware approaches in task scheduling; (b) multicloud environment that evaluates cost‐aware, multi‐objective, and QoS‐aware task scheduling; and (c) mobile cloud environment that is energy‐aware and QoS‐aware task scheduling. The analytical discussions are provided to show the advantages and limitations of the existing approaches.

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Software as a service based CRM providers in the cloud computing: Challenges and technical issues

Cited by 34 publications

References 29 publications

A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

Internet of Things and Its Applications: A Comprehensive Survey

Task scheduling mechanisms in cloud computing: A systematic review

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