Predicting service industry performance using decision tree analysis

Yeo, Benjamin; Grant, Delvin

doi:10.1016/j.ijinfomgt.2017.10.002

Cited by 51 publications

(23 citation statements)

References 73 publications

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“…The following Table 1 gives a summary of comparative study using three methods in open data domain. [6,10] Data is summarized based on the pairwise comparison matrix [7] Data is summarized based on the assign payoffs process of possible investments [19] Data type Numerical and categorical [27] Numerical and categorical [17] Numerical and categorical [20] Probability Posterior probability distribution [10] Posterior probability distribution [17] Posterior and conditional probability distribution [28…”

Section: Resultsmentioning

confidence: 99%

“…The use of decision tree analysis, furthermore, is to construct a feasible decision from the complex problems in the open data domain. A decision-tree is a decision support theory that uses a schematic tree-shaped diagram of decisions and their reasonable consequences of the conditional control arguments [19,20]. In addition, decision tree analysis can serve a number of purposes when complicated problems in the decision-making process of releasing data are found.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Comparative Study of Methods for Deciding to Open Data

Luthfi

Janssen

2019

Lecture Notes in Business Information Processing

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Governments may have their own business processes to decide to open data, which might be supported by decision-making tools. At the same time, analyzing potential benefits, costs, risks, and other effects-adverse of disclosing data are challenging. In the literature, there are various methods to analyze the potential advantages and disadvantages of opening data. Nevertheless, none of them provides discussion into the comparative studies in terms of strengths and weaknesses. In this study, we compare three methods for disclosing data, namely Bayesian-belief networks, Fuzzy multi-criteria decisionmaking, and Decision tree analysis. The comparative study is a mechanism for further studying the development of a knowledge domain by performing a feature-by-feature at the same level of functionalities. The result of this research shows that the methods have different strengths and weaknesses. The Bayesianbelief Networks has higher accuracy in comparison, and able to construct the causal relationships of the selected variable under uncertainties. Yet, this method is more resource intensive. This study can contribute to the decision-makers and respected researchers to a better comprehend and provide recommendation related to the three methods comparison.

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Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Comparative Study of Methods for Deciding to Open Data

Luthfi

Janssen

2019

Lecture Notes in Business Information Processing

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“…One of the advantages of TOE framework is its ability to enable researchers to get a broader picture of the innovation process, and this happens due to its integration ability of different factors that affect the adoption into their respective context including technology, organisation, and environment [8] In the existing literature, a considerable empirical supported has been gained by the TOE framework, used in many studies relating to different types of technology adoption [9]. Despite its broader application, the TOE framework has alone neglected the relevance of inter-organisational relationships relating to human factors and also does not consider the importance of combining factors that may address the issue of inconclusive findings [8].…”

Section: Related Workmentioning

confidence: 99%

Developing a Conceptual Model for the Intention to Adopt CC Saas

Hadi,

Othman,

Osman

2020

IJEAT

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Cloud Computing (CC) is an evolving information technology paradigm providing on-demand IT resources on a pay-as-you-go basis. A cloud computing service model called Software as a Service (SaaS) emerged to offers IT services, effectively utilise computing and power consumption while achieving performance, decreasing cost, and increasing revenue. However, the adoption rates of CC-SaaS among the organisations are inadequate, and its diffusion is not fully explored due to issues related to data security, privacy concerns and trust which affects the adoption of CC-SaaS. There is a lack of empirical studies investigating factors affecting the adoption of CC-SaaS from the organisational perspectives specifically in Iraq. Therefore, the primary aim of this study is to identify the most influencing factors for the intention to adopt CC-SaaS in Iraqi organisations. In order to meet the primary aim, such factors are reviewed and selected from the literature on a high frequency of occurrence and developed the proposed model. The result of the factors is validated by expert and the values of assessment are statistically analysed using SPSS for t-test analysis. The proposed model can give a guide for the decision makers to plan the successful adoption of CC-SaaS in the organisation

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“…The existing literature provides insight into the advantages of using DTA the decision-making process. First, DTA can generate understandable the estimation process and is easy to interpret [5,6]. Second, DTA is able to take into account both continuous and categorical decision variables [5,7].…”

Section: Theory Of Decision Tree Analysismentioning

confidence: 99%

“…In order to effectively manage and construct a decision tree based analysis, and to represent a schematic and structured way, in this paper we use four main steps in developing DTA [5][6][7], as follows: First, define a clear problem to narrow down the scope of the DTA. Relevant factors resulting in alternative solutions should be determined as well.…”

Section: 1mentioning

confidence: 99%

Decision Tree Analysis for Estimating the Costs and Benefits of Disclosing Data

Luthfi

Janssen

Crompvoets

2019

Lecture Notes in Computer Science

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The public expects government institutions to open their data to enable society to reap the benefits of these data. However, governments are often reluctant to disclose their data due to possible disadvantages. These disadvantages, at the same time, can be circumstances by processing the data before disclosing. Investments are needed to be able to pre-process a dataset. Hence, a trade-off between the benefits and cost of opening data needs to be made. Decisions to disclose are often made based on binary options like "open" or "closed" the data, whereas also parts of a dataset can be opened or only pre-processed data. The objective of this study is to develop a decision tree analysis in open data (DTOD) to estimate the costs and benefits of disclosing data using a DTA approach. Experts' judgment is used to quantify the pay-offs of possible consequences of the costs and benefits and to estimate the chance of occurrence. The result shows that for non-trivial decisions the DTOD helps, as it allows the creation of decision structures to show alternatives ways of opening data and the benefits and disadvantages of each alternative.

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Predicting service industry performance using decision tree analysis

Cited by 51 publications

References 73 publications

A Comparative Study of Methods for Deciding to Open Data

A Comparative Study of Methods for Deciding to Open Data

Developing a Conceptual Model for the Intention to Adopt CC Saas

Decision Tree Analysis for Estimating the Costs and Benefits of Disclosing Data

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