Mining survey data for SWOT analysis

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis is one of the most important tools for strategic planning. The traditional method of conducting SWOT analysis does not prioritize and is likely to hold subjective views that may result in an improper strategic action. Accordingly, this research exploits Importance-Performance Analysis (IPA), a technique for measuring customers’ satisfaction based on survey data, to systematically generate prioritized SWOT factors based on customers’ perspectives which in turn produces more accurate information for strategic planning. This proposed approach is called IPA based SWOT analysis and its development issues discussed in this report are: (1) selecting a technique for measuring importance which is one of the two main aspects of IPA since currently there are no well-established approaches for measuring importance; and (2) identifying opportunities and threats since only strengths and weaknesses can be inferred from the IPA result.The first issue is addressed by conducting an empirical comparison to analyse the performance of various techniques for measuring importance. Specifically, this thesis considers two data mining techniques namely Naïve Bayes and Bayesian Networks for measuring importance and compares their performance with other techniques namely Multiple Linear Regressions, Ordinal Logistic Regression and Back Propagation Neural Networks that have been used to derive the importance from the survey data. The comparison result measured against the evaluation metrics suggests that Multiple Linear Regressions is the most suitable technique for measuring importance.Regarding the second issue, opportunities and threats were identified by comparing the IPA result of the target organisation with that of its competitor. Through the use of IPA based SWOT analysis, it is expected that an organisation can efficiently formulate strategic planning as the SWOT factors that should be maintained or improved can be clearly identified based on customers’ viewpoints. The application of the IPA based SWOT analysis was illustrated and evaluated through a case study of Higher Education Institutions in Thailand. The evaluation results showed that SWOT analysis of the case study has a high face validity and its quality is considered acceptable, thereby demonstrating the validity of this study. Although the application of IPA based SWOT analysis was illustrated in the specific field, it can be argued that IPA based SWOT analysis can be used widely in the other business areas where SWOT analysis has been seen to be applicable and the customer satisfaction surveys are generally conducted.<br/

Mining survey data for SWOT analysis

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis is one of the most important tools for strategic planning. The traditional method of conducting SWOT analysis does not prioritize and is likely to hold subjective views that may result in an improper strategic action. Accordingly, this research exploits Importance-Performance Analysis (IPA), a technique for measuring customers’ satisfaction based on survey data, to systematically generate prioritized SWOT factors based on customers’ perspectives which in turn produces more accurate information for strategic planning. This proposed approach is called IPA based SWOT analysis and its development issues discussed in this report are: (1) selecting a technique for measuring importance which is one of the two main aspects of IPA since currently there are no well-established approaches for measuring importance; and (2) identifying opportunities and threats since only strengths and weaknesses can be inferred from the IPA result.The first issue is addressed by conducting an empirical comparison to analyse the performance of various techniques for measuring importance. Specifically, this thesis considers two data mining techniques namely Naïve Bayes and Bayesian Networks for measuring importance and compares their performance with other techniques namely Multiple Linear Regressions, Ordinal Logistic Regression and Back Propagation Neural Networks that have been used to derive the importance from the survey data. The comparison result measured against the evaluation metrics suggests that Multiple Linear Regressions is the most suitable technique for measuring importance.Regarding the second issue, opportunities and threats were identified by comparing the IPA result of the target organisation with that of its competitor. Through the use of IPA based SWOT analysis, it is expected that an organisation can efficiently formulate strategic planning as the SWOT factors that should be maintained or improved can be clearly identified based on customers’ viewpoints. The application of the IPA based SWOT analysis was illustrated and evaluated through a case study of Higher Education Institutions in Thailand. The evaluation results showed that SWOT analysis of the case study has a high face validity and its quality is considered acceptable, thereby demonstrating the validity of this study. Although the application of IPA based SWOT analysis was illustrated in the specific field, it can be argued that IPA based SWOT analysis can be used widely in the other business areas where SWOT analysis has been seen to be applicable and the customer satisfaction surveys are generally conducted.<br/

JINDEX: JSON and index search system for plant germplasm database

To facilitate the development of new varieties and conserve plant germplasm data for future needs, Thailand organizations have developed plant germplasm search systems that provide access and exchange plant genetic resource data like the international organizations. However, the development of plant germplasm search systems using traditional data warehousing creates a limitation in terms of structural flexibility and scalability, as well as search performance. Accordingly, this paper proposes a JSON and index search system for the plant germplasm database named JINDEX. JINDEX is a new approach for implementing a galaxy schema in NoSQL based a hybrid key-value/document data model. Plant germplasm data is stored in JSON files as a document data model, providing a flexible structure of genetic resources for various plants. The plant germplasm data and index files are organized as an on-disk tree structure, which can be accessed regarding a key-value data model to retrieve plant germplasm data efficiently. Experimental results showed that the JINDEX-based plant germplasm search system outperforms the previous plant germplasm search system implemented in a relational database in terms of query response time. Additionally, this JINDEX-based plant germplasm search system has been deployed since 2020, demonstrating that it can work practically

Developing SWOT analysis from customer satisfaction surveys

Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis is one of the most commonly used tools for strategic planning. It helps organizations gain a better insight of their internal and external business environment when making strategic plans and decisions. Although SWOT analysis has been widely accepted as a tool for strategic planning, the traditional method of conducting SWOT analysis does not prioritize and is likely to hold subjective views that may result in an improper strategic action. One way to make better use of the SWOT framework is to take the customer’s perspective in to account which helps the companies to ensure that their perceived capabilities are also recognized and valued by their customer. This work proposes a combination of Back Propagation Neural Network based Importance-Performance Analysis (BPNN-IPA) and SWOT analysis. The ‘Importance’ is derived by applying BPNN on a customer satisfaction survey and ‘Performance’ is computed as the mean value of customer’ s satisfaction rating. The intersection of these two components creates a two-dimensional matrix termed, IPA matrix, which can be identified as strengths and weaknesses of the company. Base on the same principle, opportunities and threats are obtained through the IPA matrix of the company’s competitor. The BPNN-IPA yields significant improvement in estimating of attribute importance compared to conventional IPA and regression-based IPA approach, thereby generating effective SWOT analysis. It is expected that this approach will provide more accurate information for strategic planning as it generates prioritized SWOT factors based on the customer’s perceptio

Attribute importance measure based on back-propagation neural network: an empirical study

Over the years, many different Importance-Performance Analysis (IPA) variations have emerged as it is a primary tool for analyzing customer satisfaction. One of the recent IPA variations is Back-Propagation Neural Network based Importance-Performance Analysis (BPNN based IPA) that utilizes BPNN to measure Importance. To investigate the performance of the BPNN based IPA, the authors compared two types of BPNN models that have one and multiple output neurons referred as BPNN (regression) and BPNN (classification) respectively, with Multiple Linear Regression (MLR). This comparison demonstrates that the BPNN (regression) does not outperform MLR in term of model accuracy and training time, yet BPNN (classification) is superior to MLR and BPNN (regression) in term of model accuracy and predictive power. This finding leads to a reconsideration of the BPNN model used in the present BPNN based IP

Importance-performance analysis based SWOT analysis

SWOT analysis, a commonly used tool for strategic planning, is traditionally a form of brainstorming. Hence, it has been criticised that it is likely to hold subjective views of the individuals who participate in a brainstorming session and that SWOT factors are not prioritized by their significance thus it may result in an improper strategic action. While most studies of SWOT analysis have only focused on solving these shortcomings separately, this study offers an approach to diminish both shortcomings by applying Importance-Performance Analysis (IPA) to identify SWOT based on customer satisfaction surveys which produces prioritized SWOT corresponding to the customers’ perception. Through the use of IPA based SWOT analysis, it is expected that a organisation can efficiently formulate strategic planning as the SWOT factors that should be maintained or improved can be clearly identified based on customers’ viewpoints. The application of the IPA based SWOT analysis was illustrated and evaluated through a case study of Higher Education Institutions in Thailand. The evaluation results showed that SWOT analysis of the case study accurately reflected the organisation's situations thereby demonstrating the validity of this study