CHAPTER 6 CONCLUSION
6.2 C
Learned from chapter 5, the results showed the 8 studied cases related to each research objectives. We have answered each of the questions proposed on chapter 1.3. It helps business management team, how to leverage the massive data created from location-based service. This study provided 8 different case for enterprise to refer to their own operation.
The materials of the LBS literature were derived from a systematic review, measured by the number of citations, as shown in Chapter 2. The whole research followed the research method in the chapter 3. Including content analysis, data collection, and data analysis.
In order to understand the management of LBS big data, this study collected 8 different type of LBS cases in chapter 4. Each of the case was described about the major applications of current marketplace. The content focus on the answering research questions, including of the features, collection and analysis methods of the big data on LBS and examine the management efforts and benefits of the use of big data results from LBS.
A very large number of data has been generated off those LBS. The LBS data sets are usually generated in real time, in large volumes and in unstructured forms. This study already described how the data features are, what technology was used, and what efforts done by management.
This research found all cases are digitalized data and real time data. May not include routing path, but contain lots of location data. Precision situational are most factors. Non-structured are data of various, defined, pre-defined, un-defined. Some are collected from social network, some are not. All cases must involve cloud computing and storage technology. Other technologies are applied depended on structure of data and computational needs. All cases may not go through specific database management and clustering technique. But, recommendation process is a must. The value was developed mainly in customer and infrastructure components.
“Customer” can experience significant value from the LBS big data and whole business
“Infrastructure” can also receive big improvement in the back of office process. The tables were collected and put on the content of chapter 5.
6.2 Contribution and management implication
The main contribution of present research is that it will help creating an advantage and
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innovation of location-based services with big data from the perspectives of service, technology, social issues, and government regulation. Several development cases of location-based services in different industries already be reviewed. Using 8 multiple cases study approach, the fundamental set of factors are influencing the development and the adoption of location-based services with big data.
Location-based services with big data are another way to bring new meaning to old products. Most companies believe that the unstructured data collected from online network system, combined with customer data from traditional sources, such as customer relationship management (CRM) or enterprise relationship management (ERM) systems. Which will be a new strategy of business operations (Mullich, 2012).
For top management team, who care about what is the most real important things of location-based service with big data? Which are the systems of recommendation and decision.
Recommendation system provided customer benefits, decision system made profits to the enterprise. A Big Data strategy is not an afterthought, but something that has to be planned ahead.
6.3 limitation and future research
The data exploded when it can be linked with other data, thus data integration is a major advantage of value. The main limitations of the study stem from the limited scope of the data sources. Since most data is directly generated in digital format today. The opportunity and the challenge are how to link data automatically and influence. Data mining, text mining are widely used in qualitative research of big data as data analysis methods, and a strongest algorithm would be a powerful tool to create value from these data. Since the information gathered for this research is based on a literature survey and industries in marketplace. To ensure the high quality of the information sources, and information gathering was done widely (Wang, 2008).
The materials of cases collected from literature and website information. The issue is concerning about the business secret. Which will not show on the public media. For example, the enterprise adopted what kind of technology in detail are not easy to access, this research lack some evidence to prove that. Even the phenomenon show them definitely used some technology.
The present research motivation, objectives and methods involved in this report were
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presented in previous chapters. The study examined the actual situation and development of location-based services in 8 different cases.
The privacy of data is another concern with increasing in the context of Big Data.
Managing privacy is effectively both a technical and a sociological problem. For user’s position records, there are strict laws governing what can and cannot be done. However, there is great public fear regarding the inappropriate use of personal data, particularly through linking of data from multiple sources. To managing these personal data should be very carefully, could be possibly conflicted with the legal. It’s a big limitation to those who want to develop a system of location-based service with big data (Agrawal, et al., 2011).
In further research will focus on the security issue. Including data store, transition, delivery, and exchange. Data security is put in place to ensure privacy in addition or protecting this data. There was and always will be an emphasis on protecting personal or company data.
One of the biggest reasons to keep data protected is because there are many enterprise that hacker want to target and breach. Data security tends to be necessary for business operation.
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