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Nowadays, communications, products, services and costs are customized through the internet technology. The main theory to continue competitiveness in the organizations is customer relationship management (CRM). CRM enables organizations to efficiently interact with customers and gather, store and examine their data for providing a complete view of them. On the other hand, the subject of cloud computing has increasingly become the bridge for the success of the CRM implementation. Therefore, this study aims to investigate the impact of cloud computing (new cloud facility, knowledge of information technology (IT), cloud security and cost) on the success of CRM systems.

The model and the questioners-based data are analyzed using the Smart PLS 3.0. The data were gathered based on 80 employees of three main agricultural companies in Iran.

The obtained results have indicated that all of the considered factors, new cloud facilities, knowledge of IT, cloud security and cost, play an important role in CRM systems’ success. Also, the evaluation and examination of the consistency and validity of the model are performed through the structural equation model.

First, the authors have conducted a study in a single region. It cannot be guaranteed that the results can be generalized to other regions. Second, for this cross-sectional study, the research design was conducted that showed constant relationships between variables. The research done for this study is cross-sectional. Third, because of time and financial restrictions, the authors have gathered data using a sample from a single location.

Proposing a new model for investigating of the impact of cloud computing (new cloud facility, knowledge of Information Technology (IT), cloud security and cost) on the success of CRM systems is the main originality of this paper.

The aim of this paper is to provide a comprehensive and detailed review of the state-of-the-art mechanisms of knowledge sharing (KS) in the supply chain (SC) field, as well as directions for future research. Briefly, this paper tries to offer a systematic and methodical review of the KS mechanisms in the SC to provide a comparative summary of the selected articles, to collect and describe the factors that have the influence on KS and SC, to explore some main challenges in this field and to present the guidelines to face the existing challenges and outlining the key areas where the KS mechanisms in SC can be improved.

In the current study, a systematic literature review up to 2018 is presented on the supply chain’s mechanisms of KS. The authors identified 21,907 papers, which are reduced to 25 primary studies through the paper-selection process.

The results showed that the KS in SC helps to increase the success of the organizations, improve employee performance, increase competitive advantage, enhance innovation and improve relationships between supplier and consumer. However, there were some weaknesses, such as staff resistance to share knowledge in the SC because of fear of job loss.

There are several limitations to this study. This study limited the search to Google Scholar. There might be other academic journals where Google does not find their paper and they can offer a more complete picture of the related articles. Finally, non-English publications were omitted from this study. It is possible that the research about the application of KS in SC can also be published in other languages. In addition, more studies need to be carried out using other methodologies such as interviews.

The paper presents a comprehensive structured literature review of the articles’ mechanisms of KS in SC. The paper’s findings can offer insights into future research needs. By providing comparative information and analyzing the current developments in this area, this paper will directly support academics and practicing professionals for better knowing the progress in KS mechanisms.

This paper aims to present a new model for solving the integrated production planning and scheduling. Usually, the two decision levels are treated sequentially because of their complexity. Scheduling depends on the lot sizes calculated at the tactical level and ignoring scheduling constraints generates unrealistic and inconsistent decisions. Therefore, integrating more detail scheduling constraint in production planning is important for managing efficiently operations. Therefore, an integrated model was developed, and two evolutionary optimization approaches were suggested for solving it, namely, genetic algorithm (GA) and the hybridization of simulated annealing (SA) with GA HSAGA. The proposed algorithms have some parameters that must be adjusted using Taguchi method. Therefore, to evaluate the proposed algorithm, the authors compared the results given by GA and the hybridization. The SA-based local search is embedded into a GA search mechanism to move the GA away from being closed within local optima. The analysis shows that the combination of simulated annealing with GA gives better solutions and minimizes the total production costs.

The paper opted for an approached resolution method particularly GA and simulated annealing. The study represents a comparison between the results found using GA and the hybridization of simulated annealing and GA. A total of 45 instances were studied to evaluate job-shop problems of different sizes.

The results illustrate that for 36 instances of 45, the hybridization of simulated annealing and GA HSAGA has provided best production costs. The efficiency demonstrated by HSAGA approach is related to the combination between the exploration ability of GA and the capacity to escape local optimum of simulated annealing.

This study provides a new resolution approach to the integration of planning and scheduling while considering a new operational constrain. The model suggested aims to control the available capacity of the resources and guaranties that the resources to be consumed do not exceed the real availability to avoid the blocking that results from the unavailability of resources. Furthermore, to solve the MILP model, a GA is proposed and then it is combined to simulated annealing.

Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.

Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.

An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.

To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

A fundamental concept of the smart city is to get the right information at the right place to make city-related decisions easier and quicker. The main goal of supply chain management (SCM) systems is to enhance the supply chain process for delivering the identified products to customers correctly in distributed organizations. In addition, new IT infrastructure such as cloud-based systems and internet of things (IoT) have changed many organizations and firms. Hence, this study aims to assess the factors that contribute to the success of SCM systems.

In this paper, the usage of urban knowledge, urban intelligent transportation systems and IT infrastructure was considered as a key factor for the success of SCM systems. For assessing the features of the model, a comprehensive questionnaire was designed. The survey questionnaires were sent to critical informers who are practical heads associated with SCM and urbanism. Of these, 315 usable responses were received, resulting in a response rate of 82.03%. The data were examined using Smart-PLS version 3.2 and IBM SPSS version 25.

The obtained results showed the high strength of the proposed model. This study found that the impact of urban ITS (safety, accessibility, information management and flexibility) is important to the success of supply chain management systems. Another important finding is that the cloud-based system (cloud security, resource virtualization, on-demand self-service and scalability) has a very important role in the success of supply chain management systems. The finding showed that the effect of IoT service variable (commercialization, mobility features, infrastructure capabilities and security and privacy) on the success of supply chain management systems is significant and positive. The findings also showed that urban knowledge (usage skills, awareness, experience and knowledge sharing) is viewed as a significant factor in the success of supply chain management systems.

The inductive nature of research methodology has introduced limitations on the generalizability of results. Therefore, it is recommended to examine the validity of this research model in other supply chains.

The statistical results support the crucial role of urban knowledge, urban intelligent transportation systems, IoT services and cloud-based systems. Therefore, aspects relating to these factors must be the focus of attention of any distributed organization in their endeavor to develop supply chain management systems. Implementing cloud based IoT through accurate and timely availability of information, can predict forecasting and planning processes, resources, logistics and support, service management and spare parts and many sub-processes in the supply chain. These technologies allow organizations to invest in manufacturing and operating processes rather than paying for the software section, which will generate more cash flow.

One of the most crucial and fundamental parts of an organization’s management is the supply chain management. The department is responsible for coordinating all units from the initial stages, such as supplying materials to the final stages, such as delivery and after-sales service. Comprehensive and credible information platforms are essential for managing a supply chain. Therefore, it is important to use integrated information systems such as IoT, cloud computing, intelligent transportation systems and more in this part of the organization management. Covering this information in a timely and accurate manner will facilitate the process and make the process more transparent. For this purpose, a model is needed to determine the relationship between technologies and supply chain management, which this study has provided a comprehensive model.

Nowadays, the Internet of Things (IoT) offers new intelligent services and business model opportunities by extending the internet connectivity into physical devices and daily objects. Recently, this technology has had a deep impact on all the aspects of human societies from industry to management and business. Therefore, the purpose of this paper is to predict the impact of using IoT services on the development of electronic business (e-business).

For evaluating the model’s elements, a questionnaire was designed. It was revised by experts with significant experiences. For statistical analysis, SmartPLS 3.2 is used.

The findings have confirmed the validity of the proposed model. The results also have indicated that the quality of IoT services (scalability, availability, reliability and ease of use), security of IoT services (trust, reputation, privacy and encryption) and IT knowledge of users (usage skills, awareness, experience and accuracy) have a positive and significant impact on development of e-business. Furthermore, the obtained results have revealed that the operating cost of IoT services (transmission time, storage capacity, functionality and stability) is significantly influenced by the development of e-business.

By capturing a number of important factors in the proposed model, this study can provide a significant theoretical influence for researchers in the related area of interest. In fact, this study provides a worthwhile direction by assessing e-business performance, which, so far, has not been well assessed in many developing countries.

From a practical perspective, the statistical results support the crucial role of the following factors: quality of IoT services, the security of IoT services, operating cost of IoT services and IT knowledge of users. Hence, aspects relating to these factors must be the focus of attention of any organization in their endeavor to development of e-business.

This study meaningfully contributes to the knowledge and literature by focusing more on development e-business and IoT as original technology for further understanding, investigating other important features and applying advanced statistical analyses technique. By doing so, this study was able to develop the current understanding regarding the main aspects of development e-business and IoT services.