Introduction
The article Factors Affecting Intention to Adopt Cloud-Based ERP from a Comprehensive Approach extensively discusses how cloud-based Enterprise Resource Planning is successful. The main aim is to convince on the benefits of incorporating the systems in organizations. It outlines the factors that promote this process and those that hinder the adoption with the help of the theoretical background. Using a research model, the article can outline the research carried out empirically to examine the innovation, the impact of the Technology Organization Environment, and the resistance characteristics associated with adopting this cloud-based ERP system. To verify the research methodology was used that involved measurements and data collection. The results were then analyzed; from the research, this cloud-based system is gaining popularity with time. Very soon, large enterprises will replace their on-premise ERP with the model of SaaS service. This gives a hint that the market is undergoing a shift in terms of generational technology.
Body
The article gives a detailed explanation of the process involved in adopting the ERP cloud-based system. This shows the strength of this article because of how the details are explained systematically. It begins by giving an overview of what the procedure entails, and this is successful with the help of the theoretical background (Ahn & Ahn, 2020). The framework gives a structure that supports the adoption of this system in this research article. It starts by introducing the theory that explains why we need to study the research about this systems adoption and validates the existence of the study. The Cloud-Based ERP and On-Premise ERP both show the significance of the transformation in technology. With the development in cloud computing technology, Cloud-Based ERP is slowly replacing the On-Premise ERP. The fact that Cloud-based ERP has many advantages compared to the latter gives a validation of why it is being adopted.
According to the article, the adoption involves the implementation perspectives that articulate the benefits and challenges of adopting this system (AlBar & Hoque, 2019). For example, recently, Adnan Albar carried out a study about the adoption of the cloud-based ERP in Saudi Arabia to better understand logistical factors associated with adoption in medium and small enterprises in the developing economies. The article continues to examine the adoption using the technology-organization-environment framework. This identifies the competitive pressure, technological readiness, and other factors that significantly influence the adoption of this system.
The article then gives the innovative theories that affect IT, which determines the rate of adoption. These innovative features have a relative advantage in the adoption rate. The model of Innovation Resistance then explains that for an adoption to occur, the system has to overcome some initial resistance (Zadeh. et al., 2018). With high innovative resistance, then there are adverse effects in adoption. The research to support the adoption of Cloud-Based ERP is then well described using the research model, and the data is analyzed to give the best results. The article is well articulated, so it is applicable and should be used for related studies.
This articles procedures and data analysis strategies give a well-illustrated image of how the research model covers this adoptions technological, organizational, and environmental contexts. Data security and observation characteristic are also included in the model (Mohd Anwer, 2019). Hypothesis concerning the findings of those contexts is then developed. The research methodology is used to verify the research model wherein the measured items concerning innovative characteristics were picked from previous studies to fit the research. Surveys helped in data collection where companies participated in the surveys. The survey questionnaires were distributed through phones and emails, and the defining features of the respondent enterprises were tabulated.
The data was then analyzed to validity using exploratory factor analysis (EFA) under the measurement models. Reliability analysis is regarded as reliable if Cronbachs alpha value is above 0.6. Descriptive statistics of measurement instruments were tabulated to show the validity and reliability of the research (Mohd Anwer, 2019). Hypothesis tests were then carried out using multiple regression analysis for verificationthe results of this help identify the relationship between cloud-based ERP skill and cloud-based ERP adoption intention.
In conclusion, the article is very substantial, and I highly recommend it to professionals to use it as a reference in related studies. It gives the interpretation of the procedures used and the strategies in the analysis of data. According to my assessment, it has comprehensively tackled the topic of cloud-based ERP system adoption.
References
Ahn, B., & Ahn, H. (2020). Factors affecting intention to adopt cloud-based ERP from a comprehensive approach.Sustainability,12(16), 6426. https://www.mdpi.com/793698
AlBar, A. M., & Hoque, M....
…the present day because those of the old days cannot have a significant impact. This means that the study acknowledges both recent and past researches.In addition, the research is extremely crucial because it has recognized both the intrinsic and extrinsic motivation factors. The study has embraced the practical motivating factors that an organization can practice to maximize its output (Nurun & Di 2017). Using the framework of hypotheses linkages derived from different motivation literature will help understand the dependent and independent variables. However, one of the weaknesses in this article is that the opinions provided do not come from any outside sources like institutions. Instead, they are all the authors opinions; the article may be biased by presenting his ideas according to his needs and interests.
Interpretation of the procedures and the data analysis used in the journal is an excellent way of evaluating this research article. The research method used is nature and data collection; according to nature, the research was quantitative (Makki & Abid 2017). This involved a descriptive to identify statistical tools and the motivating factors to validate with the help of hypothesis testing. Convenient sampling was used to collect data, and both primary and secondary data were the basis of this particular research. Preliminary data were obtained through non-disguised questionnaires that were structured, while the secondary data were from journals and articles. The study used descriptive statistics to understand the profile of the respondents in terms of demography. The mean score, in this case, was used to find the distribution of the figures average value.
The descriptive analysis incorporated various statistical tools to analyze data. Results obtained from statistical tests of significance were diagnosed in their subsequent sections. The researchers survey findings help since the strategies can be implemented to improve their effectiveness (Nurun & Dip 2017). The research also gives results that are before the initial speculations. It was concluded from the survey that employees were motivated by knowing there is career growth and development. This is unlike the earlier assumptions that money rewarding as a motivating factor was the best way.
The results also shifted to those organizations that value the competencies and skills of their employees and not their experiences. For example, Google has initiated learning academies where its employees can engage…
References
Boxall, P., & Purcell, J. (2011). Strategy and human resource management. Macmillan International Higher Education.
Khan, A., Ahmed, S., Paul, S., & Kazmi, S. H. A. (2017, July). Factors affecting employee motivation towards employee performance: A study on the banking industry of Pakistan. In International conference on management science and engineering management (pp. 615-625). Springer, Cham.
Makki, A., & Abid, M. (2017). Influence of intrinsic and extrinsic motivation on employee’s task performance. Studies in Asian social science, 4(1), 38-43.
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