5.2 Other Aspects
5.2.6 Bibliometric Analysis
Bibliometric analysis has gained relevance in the last decade for business. The emergence of software and scientific repositories, such as Scopus or the Web of Science, facilitated the investigation of business information science. This type of analysis allows working with large volumes of data with research impact. Based on this analysis, it is possible to perceive trends in publications, observe patterns and understand the structure of the existing literature. The data obtained and the bibliometric analysis help to understand and map the information. On the other hand, these data help to identify the global view of the literature, the existing gaps, observe the variants and understand the contributions to the scientific field (Donthu, Kumar, Mukherjee, Pandey, & Lim, 2021).
The software we used to perform the bibliometric analysis was VOSviewer. The software allows mapping the data collected through mapping and clustering techniques. This tool allows us to create, visualize and explore bibliometric maps. VOSviewer allows you to analyse all types of data collected in scientific repositories, such as titles and abstracts of publications, or authors and co-authors. VOSviewer has English-only language text mining functionality. To create a term map based on the selected data, the software distinguishes the following: identification of noun phrases, selection of the most relevant noun phrases, mapping and clustering of the terms, visualization of the mapping and clustering results (Eck & Waltman, 2016; Van Eck & Waltman, 2012).
We used the text mining functionality which allowed us to map terms from the 126 eligible publications. Publications were extracted in “.ris” format from each of the scientific repositories. The main criterion is to include the title and abstract of the publications. With the exception of Scopus, it was necessary to manually edit the “.ris”
extracts from EBSCO, IEEE, Taylor & Francis and WoS. Abstracts were included in these documents(Eck & Waltman, 2016; Van Eck & Waltman, 2012) (Eck & Waltman, 2016;
Van Eck & Waltman, 2012).. Other criteria were considered, as we can see in the Table 15.
Table 15 Term Mapping Criteria
Use VOSviewer
Include only eligible publications Create map based on text data
Select and include titles and abstract fields
VOSviewer version 1.6.18 126 publications
.ris format
After defining the criteria, selecting, and configuring the data, we obtained a map with different clusters, 6 in total, as we can see in Table 17.
Table 16 Create map: selection and configuration of data in VOSviewer
Choose fields Title and abstract fields
Ignore structured abstract labels Ignore copyright statements Choose counting method Full counting
Choose threshold Minimum number of occurences of a term: 7 Of the 2815 terms, 120 meet the treshold Choose number of terms 72
Verify selected terms retailer, routine, rule, supplier, management accounting, accounting benefit, agility, tco, smart factory, change, real time, firm, theory, nature, work, financial performance, rfid, effect, value, csfs, erp success, business intelligence, problem, big data, enterprise system, product, manufacturing, future research, group, information technology, csf, top management support, critical success factor, service, erp implementation, knowledge, smes, time, researcher, outcopme, sme, integration, internet, management control, implementation process, enterprise, influence, country, Chima, organisation, enterprise resource, usage, application, success, concept, order, alternative, erp project, relationship, business process management, tool, area, technology, case study, strategy, development
After defining the criteria, selecting, and configuring the data, we obtained a map with different clusters, 6 in total, as we can see in Table 17.
Table 17 Clusters
Cluster 1 Area, Business Process Management, Change, Concept, Future Research, Influence, Information Technology, Management control, Nature, Researcher, Routine, Rule, Theory, Time, Usage, Work
Cluster 2 Application, Big data, Case study, China, Internet, Manufacturing, Product, Real time, RFID, Service, Smart factory, Strategy, Technology
Cluster 3 Critical Success Factor, CSF, CSFs, Development, Enterprise, ERP implementation, Implementation process, Organisation, Outcome, SME, SMEs
Cluster 4 Accounting benefit, Alternative, Business Intelligence, Country, Enterprise system, ERP project, Group, Integration, Order, Tool, Value
Cluster 5 Agility, Effect, Enterprise resource, ERP success, Financial performance, Firm, Knowledge, relationship, Success, Top management support
Cluster 6 Problem, Retailer, Supplier, TCO
The Figure 13 shows us the map of terms created from VOSviewer:
Figure 13 Bibliometric map
These clusters are represented by different colours that represent different themes and their relationship. Node size indicates keyword relevance based on number of occurrences. In cluster 1, the most relevant key terms are Theory, Change and Time. This cluster, represented by the red colour, indicates that researchers are interested in technological innovations and the change they bring to companies. BPM is one of the key points for changes in companies and must be part of the change and restructuring of companies' business processes. Cluster 2 is represented by the green colour. The most frequent key terms are Technology, Application, Case Study, Manufacturing. This cluster reveals that researchers are dedicated to studying smart factories, because they generate large volumes of data generated by IoT. This data is analyzed through big data and using other technological tools using methods such as the case study. Cluster 3, colored green, presents Critical Success Factor, Enterprise, ERP implementation, as the most relevant terms. This group is focused on the study of CSFs and the implementation of ERP in companies, namely in SMEs. These authors seek to identify the implementation processes, through case studies, to understand how CFSs can help to successfully implement an ERP. Cluster 4, with the yellow colour, has Integration, Tool and BI as the most relevant terms. All the terms grouped here show us that the authors focus their studies on IS, and it is important to use BI and other technological tools to benefit companies. The integration between the different systems will create value for the companies themselves. The terms with the highest occurrence in cluster 5 are Agility, Effect, Firm and ERP success. This group is focused on the effect that IS, namely ERP, have on companies' businesses. The knowledge shared by the different users is very important, as this agility and flexibility demonstrates the good relationship between the different professionals. Cluster 6 has as main occurrences the terms Problem and Supplier.
This reflects that there are researchers who care about ERP suppliers and the problems they can solve. They bring answers to companies that are diverse and responsive to their needs.
6 CONCLUSION
ERP systems have evolved since the 1990s. There are some studies that show the evolution of these systems, revealing the results of the last decades. To understand the evolution of these systems in the last decade, it was necessary to carry out a comprehensive study of the literature published between 2011 and 2021. It was important to cover publications in the most diverse areas, considering the previously defined criteria.
We had several limitations during the research and development of the work. Access to scientific repositories was limited, as we only used those available in the B-on catalogue.
However, the scientific repository is very comprehensive and consequently this limitation may not have a significant impact on the results. The PRISMA methodology was a good way to achieve our goals although it has a rigid structure to follow. The eligibility criteria were a limitation as there were several restrictions that had to be fulfilled. This work was limited to the reduced time of search, collection, and treatment of data, by reading all eligible publications due to the need to categorize the studies, by the small number of team members, and, finally, the risk of bias led to some unbalanced results (João & Belfo, 2022).
ERP systems are technologies that allow organizations to increase their competitiveness.
New business processes are emerging, the complexity of which requires more complex implementations. This fact represents a great challenge for the companies themselves.
The adoption of an ERP requires conscious and responsible decision making. Over the last decades, we have found publications that provide a lot of data and information about different ERP providers, about the available infrastructures, or even about the consumption of resources necessary for the adoption and implementation of these systems. The data presented contribute to consolidate the knowledge of organizations, allowing the strategic reorganization and business processes, considering the major concerns identified. Organizations will always have the challenge and the opportunity to explore and learn about other perspectives of case studies, for example, learn about new tools and technological innovations, manage, and share knowledge. With this knowledge base, organizations can better manage the risks, the implementation, the integration of different systems and make the selection decision using planning strategies with the objective of obtaining a great return on investment (João & Belfo, 2022).
The academy has been contributing a lot with new publications on ERP systems. This is an interdisciplinary topic and researchers in different disciplines have collaborated. From na academic perspective, it is important to understand what studies exist, what disciplines are dedicated to studying ERP systems, what are the most relevant studies in recent decades, how ERP has evolved, what are the changes, challenges, or opportunities of adoption of the ERP. This work thus contributes to increasing knowledge on major concerns, providing update and consistent information. We help to collect data with many relevant references, map the progress of this knowledge in the last decade and identify the research gaps that exist in this area and add value to the research field. We also provide relevant information to verify the research and indicate major concerns and topics that require further investigation (João & Belfo, 2022).
Future work should look to this work as a source of knowledge and references, as it presents updated data and information on ERP systems. Investigators should spend more time studying the major concerns with less relevance, which are the cases of Value, Customer satisfaction and Maintenance, or studying the less relevant phases, which is the case of Maintenance and Retirement. It would also be interesting to challenge both Academia and Practitioners to work together to, for example, optimize infrastructure or systems maintenance, always with a focus on value creation.
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