Development of a Web-Based Strategic Management Expert System

In this paper, we present the development of a Web-based expert system, StrategyAdvisor Cloud, to support strategic management decision-making. The system was developed using a multistage methodology that builds upon knowledge graphs, where knowledge acquisition and rule base construction by project members with different roles, capabilities, and skills can be facilitated through customized visual languages. The methodology systematizes knowledge acquisition and knowledge representation for each stage, coupled with algorithms for the transformation of knowledge graphs between successive stages. The developed expert system and the development process are described in detail in the paper and its supplement, to serve as guidance in the development of similar systems in future.

Please click here to download the final draft of the article.

Please click here to download the supplement of the article.

 

Please cite the paper as follows:

Irdesel, l., Ertek, G., Demirelli, A., Kailas, L., Lekesiz, A., Shuvo, R.U. (2023). Development of a Web-Based Strategic Management Expert System Using Knowledge Graphs. In: Yang, XS., Sherratt, R.S., Dey, N., Joshi, A. (eds) Proceedings of Eighth International Congress on Information and Communication Technology. ICICT 2023. Lecture Notes in Networks and Systems, vol 693. Springer, Singapore. https://doi.org/10.1007/978-981-99-3243-6_48

A Predictive Data Analytics Methodology for Online Food Delivery

Online food delivery (OFD) has become a popular and profitable e-business category due to the rising demand for online food delivery. People are increasingly ordering food online, especially in urban areas and on college campuses. Using data from online food delivery services, one can analyze and predict the values of key performance indicators (KPIs). In the study presented in this paper, we developed a systematic methodology to analyze and predict such KPIs using various classification and regression algorithms. We found that, for the case study we analyzed, Random Forest (RF) consistently ranked as the best algorithm for regression and classification in predicting most of the KPIs. The methodology we introduce and illustrate in the paper can be adapted and extended to similar problems to reveal potential operational issues and identify the possible root causes of such problems.

Please click here to download the final draft of the article.

Please Cite as Follows:
M. A. Akasheh, N. Eleyan and G. Ertek, “A Predictive Data Analytics Methodology for Online Food Delivery,” 2022 Ninth International Conference on Social Networks Analysis, Management and Security (SNAMS), Milan, Italy, 2022, pp. 1-7, doi: 10.1109/SNAMS58071.2022.10062613.

A Data Analytics Methodology for Benchmarking of Sentiment Scoring Algorithms in the Analysis of Customer Reviews

Due to the digitalization, there exists an increased amount of user-generated content on the Internet, where people express their opinions on various topics. Sentiment analysis is the statistical and analytical examination of human emotions and opinions regarding a certain subject. Our study extends the literature by developing a data analytics methodology for the benchmarking of sentiment scoring algorithms in the context of online customer reviews. We demonstrate the applicability of the methodology using Amazon product reviews as the source data. Analyzing text-based content such as Amazon customers’ reviews through text analytics and sentiment analysis can help Amazon and other online retailers to discover valuable actionable insights regarding their products. The contributions of this study are twofolds: to examine the predictive power of machine learning (ML) algorithms with respect to predicting sentiment scores and to analyze patterns in the differences between scores obtained from different sentiment scoring algorithms.

Please click here to download the final draft of the article.

Please Cite as Follows:

Abou-Kassem, T., Alazeezi, F.H.O., Ertek, G. (2023). A Data Analytics Methodology for Benchmarking of Sentiment Scoring Algorithms in the Analysis of Customer Reviews. In: Yang, XS., Sherratt, R.S., Dey, N., Joshi, A. (eds) Proceedings of Eighth International Congress on Information and Communication Technology. ICICT 2023. Lecture Notes in Networks and Systems, vol 693. Springer, Singapore. https://doi.org/10.1007/978-981-99-3243-6_46

Analytical Modeling and Empirical Analysis of Binary Options Strategies

This study analyzes binary option investment strategies by developing mathematical formalism and formulating analytical models. The binary outcome of binary options represents either an increase or a decrease in a parameter, typically an asset or derivative. The investor receives only partial returns if the prediction is correct but loses all the investment otherwise. Mainstream research on binary options aims to develop the best dynamic trading strategies. This study focuses on static tactical easy-to-implement strategies and investigates the performance of such strategies in relation to prediction accuracy, payout percentage, and investment strategy decisions.

Click to download the open-access article:

Ertek G, Al-Kaabi A, Maghyereh AI. “Analytical Modeling and Empirical Analysis of Binary Options Strategies”. Future Internet. 2022; 14(7):208. https://www.mdpi.com/1999-5903/14/7/208

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Analyzing a Decade of Wind Turbine Accident News with Topic Modeling

Rüzgar enerjisinin önemli bir yenilenebilir enerji kaynağı olarak önemine ve büyümesine rağmen, rüzgar türbinlerinin kaza ve arıza şeklindeki riskleri üzerine yapılan araştırmalar sınırlı ilgi görmüştür. Bu bağlamda veri analitiğini metodolojik olarak uygulayan araştırmalar azdır. Burada sunulan araştırma, seçilmiş 721 rüzgar türbini kazası ve arıza haberinden oluşan bir metin külliyatının oluşturulması üzerine, tablo analizi, görselleştirme, metin madenciliği ve makine öğrenimini birleştiren özel olarak geliştirilmiş bir veri analitiği çerçevesi geliştirir ve uygular. Rüzgar türbini kazası haberlerinde yinelenen temaları belirlemek ve sınıflandırmak için ilk kez konu modelleme uygulandı ve ölüm ve yaralanma ile ilişkili bağlamsal terimleri belirlemek için çağrışım madenciliği uygulandı. Tablosal ve görsel analizler, kazaları konumla (açık denizde ve karada), rüzgar türbini yaşam döngüsü aşamalarıyla (nakliye, inşaat, işletme ve bakım) ve ölüm ve yaralanma vakalarıyla ilişkilendirir. İçgörülerden biri olarak, operasyon ve nakliye sırasında daha fazla olayın meydana geldiği tespit edildi. Konu modelleme sayesinde ölüm ve yaralanmalarla en çok ilişkilendirilen konular ortaya çıkarıldı. Sonuçlar rüzgar türbini üreticilerine, hizmet sağlayıcılara, enerji şirketlerine, sigorta şirketlerine, devlet kurumlarına, kar amacı gütmeyen kuruluşlara, araştırmacılara ve rüzgar enerjisi sektöründeki diğer paydaşlara fayda sağlayabilir.

Lütfen bu yazıdan şu şekilde alıntı yapın  (indirmek için tıklayın) :

Ertek G, Kailas L. On Yıllık Rüzgar Türbini Kaza Haberlerini Konu Modellemeyle Analiz Etmek. Sürdürülebilirlik . 2021; 13(22):12757. https://doi.org/10.3390/ su132212757
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A Scoring Approach for the Assessment of Study Skills and Learning Styles

This paper presents the application of a scoring method and algorithm, adapted from the domain of financial risk management, for the computer-based assessment of study skills and learning styles of university students. The goal is to provide a single score that summarizes the overall intensity of a student’s study skills and, in effect, develop a deeper understanding of the relation between learning styles and study skills. The dimensionality reduction obtained through the scoring algorithm also enables comparing the single-dimensional study skill scores of students for various learning styles. The algorithm computes a weight for each study skill to measure its linear contribution to the overall study skill score, also providing a natural ranking of various study skills with respect to impact on total score. Statistical tests have been conducted to measure the differences in scores for various styles in Kolb’s four-region and nine-region models. The results suggest that students with different learning styles can have statistically significant differences in their overall study skill scores. The primary contribution of the study is illustrating how a scoring approach, based on unsupervised machine learning, can enable a deep understanding of learning styles and development of educational strategies.

Please cite this paper as follows (Click the links to download):

Göğüş, A., Ertek, G. (2020). A Scoring Approach for the Assessment of Study Skills and Learning Styles. International Journal of Information and Education Technology, Vol. 10, No. 10, October 2020

 

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Beyond the Pandemic: How can Private Universities Transform with Online Education

The recent developments, due to the COVID-19 pandemic, resulted in an unexpectedly sudden and complete shift to online education all around the world. Web-based Learning Management Systems (LMS) (such as BlackBoard and Moodle) and broadcasting systems (such as Webex and GoToWebinar), have proven that the technological infrastructure is fundamentally there. This is especially true for higher education disciplines which do not require 3D physical interaction with humans, equipment, or materials. […} Online education has its advantages and disadvantages. The most major advantage of online education with respect to financials is that it digitally encapsulates some of the core functions of the instructor and can digitally amplify, multiply, and deliver these encapsulated functions at minimal costs. Furthermore, if effectively designed and delivered, online education can be as good as or better than face-to-face instruction?

Please cite this paper as follows (click the links to download in and ):

Ertek, G. and Belghiti-Mahut, S. (2020). Beyond the Pandemic: How can Private Universities Transform with Online Education. Harvard Business Review Arabia. Available under (in Arabic) and (in English).

 

 

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Graph-Based Visualization of Stochastic Dominance in Statistical Comparisons

In this paper, a graph visualization scheme and methodology is proposed for representing, understanding, and interpreting the statistical comparison of means and the resulting stochastic dominance. The practicality and applicability of the visualization scheme and the methodology is illustrated through a case study, with data coming from higher education institutes in the United States of America (U.S.A.). The objective of the research is to make statistical results more accessible and readable, enabling the visual derivation of actionable insights.

Keywords: graph visualization; graph drawing; stochastic dominance; hypothesis testing; higher education.

Please cite this paper as follows: (click to download)

Ertek, G., Tokdemir, G., and Hammoudi, M. M. (2019) “Graph-Based Visualization of Stochastic Dominance in Statistical Comparisons,” 2019 IEEE/ACS 16th International Conference on Computer Systems and Applications (AICCSA), Abu Dhabi, United Arab Emirates, 2019, pp. 1-7, doi: 10.1109/AICCSA47632.2019.9035354.

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Mind the Perception Gap: An Integrative Performance Management Framework for Service Supply Chains

Download the full published paper from Emerald.

Download the abstract & developed framework as pdf.

Visit the website or the Research Gate page of the paper.

Purpose – A perception gap refers to the differences in perception among the stakeholders regarding any aspect of the supply chain relationship. This paper investigates the perception gap among service supply chain partners relating to the relative importance of key performance indicators (KPIs) and the association of this gap with service performance.

Design/methodology/approach – This paper presents an integrative framework that combines statistical methods and data envelopment analysis (DEA) for computing perception and performance gaps, and for identifying the association between the gaps. The study follows a Middle-range theorizing (MRT) research approach where general inferences are induced from instances, and a theory can be developed from the observation of empirical reality.

Findings – Analysis of data from a leading global insurance service supply chain suggests that perception gap exists and can be recognized as a factor associated with performance gaps. The results suggest that the perception gap not only affects performance but can also be tracked as a meta-KPI to improve performance throughout the service supply chain.

Implications – The key implication of the presented research is that service companies can identify and resolve the differences in perceptions regarding the importance of the KPIs, by methodologically computing the gaps and tracking them as meta-KPIs.

Originality/value – The study extends the theoretical boundary of supply chain performance management by introducing the perception and performance gaps as novel meta-KPIs. These meta-KPIs can be computed through the integrative framework developed in the study.

Keywords Perception gap, Key performance indicators (KPI), Integrative performance management, Data envelopment analysis (DEA), Service supply chain, Middle-range theorizing (MRT).

Please cite this paper as follows (click to download from Emerald):

Lu, D., Asian, S., Ertek, G., & Sevinc, M. (2019). Mind the perception gap: An integrative performance management framework for service supply chains. International Journal of Physical Distribution & Logistics Management, 49(1), 33-51.

Download the full published paper from Emerald.

Download the abstract & developed framework as pdf.

Visit the website or the Research Gate page of the paper.

 

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Location-Based Pricing and Channel Selection in a Supply Chain: A Case Study from the Food Retail Industry

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Many retailers nowadays operate in an Internet-enabled dual-channel supply chain setting, referred to as “click and mortar”. In such a structure, products and services are delivered through both online B2C (business-to-consumer e-tail) and offline B2C (traditional brick and mortar retail) channels. In this paper, we develop and present a unified modeling approach that reflects a real-world dual-channel supply chain in the food retail industry. Motivated by the actual business operations of a case study, we incorporate the spatial locations of customers, as well as other logistics and operational costs, into the service provider’s pricing and the customers’ channel choice decisions. We develop two models, namely the benchmark and proposed models, and conduct extensive numerical experiments with parameter values centered on actual values. The results reveal that ratio of online and offline profit to the total dual-channel profit vary significantly, depending on the locations of customers and the values of the logistics costs. In addition, our statistical and visual analysis suggest that by jointly optimizing the logistics and operational processes, the service provider can achieve a considerably high profit through both channels, without necessarily expanding the size of its geographical service areas.

Please cite this paper as follows (click to download):

Wei, C., Asian, S., Ertek, G., Hu, Z.-H. (2018) Location-based pricing and channel selection in a supply chain: a case study from the food retail industry. Annals of Operations Research. https://doi.org/10.1007/s10479-018-3040-7

 

 

 

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