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Türk üniversitelerinin aday öğrenci web sayfalarının erişilebilirlik, kullanılabilirlik ve güvenlik açısından değerlendirilmesi
(2022) Medeni, Tunç Durmuş; Peker, Serhat; Medeni, İhsan Tolga; Macakoglu, Sevval Seray
Üniversitelerin aday öğrenci web sayfaları sosyal ve akademik anlamda paydaşlarına bilgi sağlama konusunda önemli bir iletişim kaynağıdır, bu sebeple bu sayfaların kullanımının kolay, güvenli ve erişilebilirlik standartlarına uygun olması beklenir. Bu makale, Türkiye’deki üniversitelerin aday öğrenci web sayfalarının erişilebilirlik, kullanılabilirlik ve güvenlik değerlendirmesini sunmaktadır. Bu amaçla, üniversitelerin aday öğrencilerine yönelik 147 adet web sayfası tespit edilmiş ve çeşitli otomatik test araçları ile değerlendirilmiştir. Ayrıca, değerlendirme sonrası üniversitelerin benzer davranış kalıplarının belirlenmesi amacıyla kümeleme analizi yapılmıştır. Sonuçlar, devlet ya da vakıf fark etmeksizin üniversitelerin büyük çoğunluğunun erişilebilirlik ve kullanım kalitesine daha az dikkat ettiğini göstermiştir. Değerlendirilen web sayfalarının WCAG 2.0 yönergesine göre düşük uyumluluk seviyesine sahip olduğu görüldü. Güvenlik açısından kritik bir sorun tespit edilmemiştir ancak geliştirilmesi gereken belirli noktalar bulunmuştur. Ayrıca bu çalışma, web sayfalarının erişilebilirlik, kullanılabilirlik ve güvenlik ihlallerin çözülebilmesi için geliştiricilere ve yöneticilere bazı değerli öneriler sunmaktadır.
A machine learning framework for data-driven CRM
(Springer, 2022) Peker Serhat; Kart Özge
In today’s digital world, enterprises accumulate large quantiles of customer data which drives firms to implement data-driven CRM strategies to manage customer relationships. In CRM, machine learning techniques are widely used as a tool for using customer data and thereby acquiring knowledge from such data. In this context, this research presents a holistic framework for the implementation of machine learning methods in data-driven CRM applications. The proposed framework relies on past transactional data of customers and employs state-of-art machine learning techniques. This research serves as a foundation for future studies on data-driven CRM applications utilizing machine learning techniques. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Kiyaslio: a gamified mobile crowdsourcing application for tracking price dispersion in the grocery retail market
(Emerald Group Publishing Ltd, 2022) Macakoğlu, Şevval Seray; Çınar, Burcu Alakuş; Peker, Serhat
Purpose In the recent years, the rapid growth of the grocery retailing industry has created a great heterogeneity in prices across sellers in the market. Online price comparison agents which are key mechanisms to solve this problem by providing prices from different sellers. However, there are many sellers in the grocery industry do not offer online service, and so it is impossible to automatically retrieve price information from such grocery stores. In this manner, crowdsourcing can become an essential source of information by collecting current price data from shoppers. Therefore, this paper aims to propose Kiyaslio, a gamified mobile crowdsourcing application that provides price information of products from different grocery markets. Design/methodology/approach Kiyaslio has been developed through leveraging the power of crowdsourcing technology. Game elements have also been used to increase the willingness of users to contribute on price data entries. The proposed application is implemented using design science methodology, and it has been evaluated through usability testing by two well-known techniques which are the system usability scale and the net promoter score. Findings The results of the usability tests indicate that participants find Kiyaslio as functional, useful and easy to use. These findings prove its applicability and user acceptability. Practical implications The proposed platform supports crowd sourced data collection and could be effectively used as a tool to support shoppers to easily access current market product prices. Originality/value This paper presents a mobile application platform for tracking current prices in the grocery retail market whose strength is based on the crowdsourcing concept and incorporation of game elements.
ICT adoption scale development for SMEs
(Mdpi, 2022) Özşahin, Mehtap; Çallı, Büşra Alma; Coşkun, Erman
Information systems research lacks a validated scale for assessing and measuring the adoption of information and communication technologies (ICTs) by small- and medium-sized enterprises (SMEs). The relevant literature is limited in studies mainly concentrating on developing country settings. Furthermore, the emergence of new technological elements and increasing digitalization and digital transformation efforts in the last two years have changed how an organization utilizes and adopts ICTs. Therefore, it is inevitable that the conceptual dimensions proposed in the previous literature and the definitions of these dimensions will also alter. Hence, it is essential to revisit and validate the prior work and enhance it based on current vitality and developments. This study developed and validated a scale for measuring ICT adoption and digitalization for SMEs in a developing country context. The researchers followed an eight-step scale development procedure: (1) comprehensive literature review on ICT adoption and digitalization; (2) identification of dimensions of the level of ICT adoption and digitalization; (3) generation of items; (4) item refinement through focus group; (5) pretest of the measurement; (6) scale purification; (7) data collection; and (8) measurement evaluation. Within the Turkish setting, the ICT adoption scale was determined to have sufficient reliability and validity. Data for this study were gathered from 421 respondents of 219 Turkish SMEs. Supporting the multidimensionality of ICT adoption, 14 items and five dimensions (communication, internal integration, integration with customers, interorganizational integration, and strategic integration) constituted the ICT adoption construct. Considering the dominance of conceptual frameworks that were proposed based on developed countries and the prevalence of unidimensional constructs in the field, the developed multidimensional scale is expected to contribute significantly. Practitioners and policymakers can utilize the suggested scale to discover areas where specific changes are required for the digital transformation in SME utilization efforts that need attention. The outcomes can be applied to industrial sectors and different geographic contexts. By considering stage-based integration, the developed scale can also be used in future studies to investigate the effects of different variables on the extent of ICT adoption and the impact of ICTs on several organizational outcomes.
Do generative leadership and digital literacy of executive management help flourishing micro and small business digital maturity?
(Canadian Inst Knowledge Development - Cikd, 2022) Calli, BUsra Alma; Ozsahin, Mehtap; Coşkun, Erman; Arik, Ahmet Rifat
Today, every firm and organization must digitally transform in order to survive and deal with increasing competition and dynamic market conditions. Digital transformation is not easy to achieve, and many factors play an important role in the successful digital transformation of firms. Leaders' leadership styles and characteristics play a crucial role in digital transformation. This study examines the effects of generative leadership and digital literacy of executive management on the digital maturity of micro and small firms based on the Upper Echelons Theory. Sub-dimensions of digital maturity are also considered and searched to provide a more detailed analysis. The research utilized a survey method and was conducted with 121 upper, middle, and first-line managers of 93 micro and small-size firms operating in the Marmara Region of Turkey. Frequency, factor, regression, and validity and reliability analyses through the SPSS package program were used. The results are two folds. First, generative leadership and digital literacy of executive management help flourish digital maturity when searched independently. Second, the study results indicate that the digital literacy of executive managers has a mediating effect on the relationship between generative leadership and digital maturity. Furthermore, the study proves the mediating effect on digital maturity's technological, strategic, and cultural maturity sub-dimensions. With these findings in micro and small businesses, the study comprehensively contributes to the current knowledge in this domain. (C)CIKD Publishing
Accessibility, usability, and security evaluation of universities' prospective student web pages: a comparative study of Europe, North America, and Oceania
(Springer Heidelberg, 2022) Macakoğlu, Şevval Seray; Peker, Serhat; Medeni, İhsan Tolga
Universities' prospective student web pages aim to disseminate information about their academic and social opportunities to their stakeholders; therefore, they must be accessible, of high quality of use and reliable. This article presents the accessibility, usage performance, and security analysis of prospective student web pages of 330 universities from three continents, namely Europe, North America, and Oceania. For this purpose, university websites were selected based on the Webometrics ranking, and online automated test tools were used. The results showed that websites at universities in North America paid more attention to accessibility and quality of use on prospective student web pages, followed by Oceanian and European websites. Evaluated websites had low compliance levels according to the WCAG 2.0 guideline. No major problems were identified in terms of usability and security, but there were certain points for improvement. Moreover, we present and discuss recommendations to developers and administrators for websites to resolve accessibility, usability, and security breaches and provide information equally to all stakeholders. Hence, this analysis report provides feedback to web developers to improve accessibility, quality of use, and security issues of university websites and their prospective student web pages.
Accessibility evaluation of university hospital websites in Turkey
(Springer Heidelberg, 2022) Macakoğlu, Şevval Seray; Peker, Serhat
Hospital web pages serve as an interactive communication resource to meet the needs of patients, healthcare professionals and other stakeholders. The aim of this study is to present the accessibility analysis of 58 university hospital websites in Turkey. For this purpose, websites of the selected university hospitals were analyzed using two different online automated testing tools. The results showed that university hospital websites in Turkey had low compliance levels according to the WCAG 2.0 guidelines. Most of the websites did not even meet the minimum requirements for compliance level A. In addition, almost all of the websites had broken links and about a third of the websites had problems with accessing from mobile devices. Moreover, some important clues that draw attention to the accessibility problems of websites are also discussed in this study. Hence, the results of this study provide feedback to developers and administrators to improve the accessibility of these websites.
Predicting firms' performances in customer complaint management using machine learning techniques
(Springer International Publishing Ag, 2022) Peker, Serhat
With the globalization and more intense increasing competition, customer relationship management (CRM) is an important issue in today's business. In this manner, managing customer complaints which is a critical part of CRM presents firms with an is an opportunity to make long-lasting and profitable relationships with customers. In this context, the aim of this paper is to predict firms' performances in online customer complaint management using machine learning algorithms. This study utilizes data obtained from Turkey's largest and well-known third-party online complaint platform and employs three popular machine learning classifiers including decision tree (DT), random forests (RF) and support vector machines (SVM). The results show that the RF algorithm performed better in firms' performance prediction compared to other ML algorithms.
Prioritizing use cases for development of mobile apps using AHP: A case study in to-do list apps
(Springer, 2019) Yıldırım, Onur; Peker, Serhat
With the rapid development of communication technologies, the uses of mobile apps have increased in a significant manner over the past few years. Every day many different types of mobile apps are uploaded to mobile application markets. However, it is very difficult for the apps to stay competitive and survive in these marketplaces. Covering the requirements fitting the needs of users is one of significant factors in mobile apps’ success in the market. In this regard, this study aims to use Analytic Hierarchy Process (AHP) to evaluate the use cases for the development of mobile apps. The results show that AHP provides an efficient tool which can be used to determine importance of the requirements in mobile apps considering users’ preferences. © 2019, Springer Nature Switzerland AG.
Customer churn prediction using deep learning
(Springer Science and Business Media Deutschland GmbH, 2021) Seymen, Ömer Faruk; Doğan, Onur; Hızıroğlu, Abdülkadir
Churn studies have been used for years to achieve profitability and to establish a sustainable customer-company relationship. Deep learning is one of the contemporary methods used in churn analysis due to its ability to process huge amounts of customer data. In this study, a deep learning model is proposed to predict whether customers in the retail industry will churn in the future. The model was compared with logistic regression and artificial neural network models, which are also frequently used in the churn prediction studies. The results of the models were compared with accuracy classification tools, which are precision, recall and AUC. The results showed that the deep learning model achieved better classification and prediction success than other compared models. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
The effects of the content elements of online banner ads on visual attention: Evidence from an-eye-tracking study
(MDPI, 2021) Peker, Serhat; Menekse Dalveren, Gonca Gokce; İnal, Yavuz
The aim of this paper is to examine the influence of the content elements of online banner ads on customers' visual attention, and to evaluate the impacts of gender, discount rate and brand familiarity on this issue. An eye-tracking study with 34 participants (18 male and 16 female) was conducted, in which the participants were presented with eight types of online banner ads comprising three content elements-namely brand, discount rate and image-while their eye movements were recorded. The results showed that the image was the most attractive area among the three main content elements. Furthermore, the middle areas of the banners were noticed first, and areas located on the left side were mostly noticed earlier than those on the right side. The results also indicated that the discount areas of banners with higher discount rates were more attractive and eye-catching compared to those of banners with lower discount rates. In addition to these, the participants who were familiar with the brand mostly concentrated on the discount area, while those who were unfamiliar with the brand mostly paid attention to the image area. The findings from this study will assist marketers in creating more effective and efficient online banner ads that appeal to customers, ultimately fostering positive attitudes towards the advertisement.
Designing a data warehouse for earthquake risk assessment of buildings: A case study for healthcare facilities
(2021) Özcan, Mert; Peker, Serhat
Since earthquake is one of the most dangerous natural phenomena, it is necessary to be prepared for the negative consequences of the earthquake in advance. It is very important that healthcare facilities must continue to provide service during and after an earthquake. Therefore, this study focuses on designing a data warehouse model for the earthquake risk assessment of healthcare facilities which are needed much more than other public buildings phys-ically. The proposed design utilizes a fact constellation schema model and take a public legislation containing principles regarding identification of risky buildings. This solution can provide a repository for data regarding earthquake risk assessment from different operational systems and play a key role in supporting critical decision-making process.
A qualitative study on entrepreneurs' characteristics and organizational factors affecting digitalization in smes: A sampling of Yalova
(Mehmet Akif Ersoy Univ, 2020) Özşahin, Mehtap; Coşkun, Erman; Alma Calli, Busra
Digital transformation (DT) is vital for SMEs as well as large companies and it must follow digitization and digitalization phases. Adoption and implementation of DT and pre-phases in SMEs is largely depend on the information and communication technologies (ICTs) awareness and competence level of owner, organization's innovativeness level, and ICT capability. This study was conducted in Yalova with 51 micro and small SMEs operating in various sectors aims to examine these four factors. It uses semi-structured face to face interviews and utilizes qualitative-quantitative analysis methods. Descriptive-interpretive analysis, regression, and frequency analyses are utilized. According to the findings, entrepreneurs first associate the word ICT with the concept of technology and then the concepts of efficiency/productivity. While entrepreneurs, who consider themselves and their company weak in terms of ICT capability and competence, match the concept of ICT with social media, technology and e-commerce concepts in general; those who perceive their organizations' level of ICT capability high mostly associate ICT with the concepts of communication, technology, information age, social media, efficiency and innovation. The factors affecting the ICT adoption of SMEs are the entrepreneur's ICT competence level, the size and the age of the organization and its level of innovativeness.
A comparison of neural network approaches for network intrusion detection
(Springer International Publishing Ag, 2020) Oney, Mehmet Uğur; Peker, Serhat
Nowadays, network intrusion detection is an important area of research in computer network security, and the use of artificial neural networks (ANNs) have become increasingly popular in this field. Despite this, the research concerning comparison of artificial neural network architectures in the network intrusion detection is a relatively insufficient. To make up for this lack, this study aims to examine the neural network architectures in network intrusion detection to determine which architecture performs best, and to examine the effects of the architectural components, such as optimization functions, activation functions, learning momentum on the performance. For this purpose, 6480 neural networks were generated, their performances were evaluated by conducting a series of experiments on KDD99 dataset, and the results were reported. This study will be a useful reference to researchers and practitioners hoping to use ANNs in network intrusion detection.
A framework for sustainable and data-driven smart campus
(Scitepress, 2020) Köstepen, Zeynep Nur; Akkol, Ekin; Doğan, Onur; Bitim, Semih; Hızıroğlu, Abdülkadir
As small cities, university campuses contain many opportunities for smart city applications to increase service quality and use of public resources efficiency. Enabling technologies for Industry 4.0 play an important role in the goal of building a smart campus. The study contributes to the digital transformation process of.Izmir Bakircay University which is a newly established university in Turkey. The aim of the study is to plan a road map for establishing a smart and sustainable campus. A framework including an architectural structure and the application process, for the development of a smart campus have been revealed in the study. The system application is designed to be 3 stages. The system, which is planned to be built on the existing information systems of the university, includes data collection from sensors and data processing to support the management processes. The proposed framework expects to support some value-added operations such as increasing personnel productivity, increasing the quality of classroom training, reducing energy consumption, accelerating interpersonal communication and finding the fastest solution to the problems on campus. Therefore, not only a smart campus but also a system is designed for sustainability and maximum benefit from the facilities.
Grouping OECD countries based on energy-related variables using k-means and fuzzy clustering
(Springer, 2018) Hızıroğlu, Abdülkadir; Kapusuzoğlu, Ayhan; Cankal, Erhan
The main purpose of this study is to examine the relationships between energy consumption, CO2 emission and economic growth for 28 OECD countries and to form clusters based on the findings. The study is carried out under the 1990-2010 period, considering the annual data, the average annual values for each country are calculated and the countries are grouped by taking into account the main energy variables. This study examined OECD countries into three groups to form more specific clustering, rendering to test the hypotheses in current empirical studies, and examining the relationships of the interacted variables for within and inter-cluster countries.
An empirical assessment of customer lifetime value models within data mining
(Univ Latvia, 2018) Hızıroğlu, Abdülkadir; Şişci, Merve; Cebeci, Halil Ibrahim; Seymen, Ömer Faruk
Customer lifetime value has been of significant importance to marketing researchers and practitioners in specifying the importance level of each customer. By means of segmentation which could be carried out using value-based characteristics it is indeed possible to develop tailored strategies for customers. In fact, approaches like data mining can facilitate extraction of critical customer knowledge for enhanced decision making. Although the literature has several analytical lifetime value models, comparative assessment of the existing models especially within the context of data mining seems a missing component. The aim of this paper is to compare two different customer lifetime value models within data mining. The evaluation was carried out within the context of customer segmentation using a database of a company operating in retail sector. The results indicated that two models yield the same segmentation structure and no statistical differences detected on the select control variables. However, the remaining model produced rather different segmentation results than their peers and it was possible to identify the most lucrative model according to the statistical analyses that were carried out on the select control variables.
A combined approach for customer profiling in video on demand services using clustering and association rule mining
(IEEE-Inst Electrical Electronics Engineers Inc, 2020) Güney, Sinem; Peker, Serhat; Turhan, Çiğdem
The purpose of this paper is to propose a combined data mining approach for analyzing and profiling customers in video on demand (VoD) services. The proposed approach integrates clustering and association rule mining. For customer segmentation, the LRFMP model is employed alongside the k-means and Apriori algorithms to generate association rules between the identified customer groups and content genres. The applicability of the proposed approach is demonstrated on real-world data obtained from an Internet protocol television (IPTV) operator. In this way, four main customer groups are identified: high consuming-valuable subscribers, less consuming subscribers,less consuming-loyal subscribers and disloyal subscribers. In detail, for each group of customers, a different marketing strategy or action is proposed, mainly campaigns, special-day promotions, discounted materials, offering favorite content, etc. Further, genres preferred by these customer segments are extracted using the Apriori algorithm. The results obtained from this case study also show that the proposed approach provides an efficient tool to form different customer segments with specific content rental characteristics, and to generate useful association rules for these distinct groups. The proposed combined approach in this research would be beneficial for IPTV service providers to implement effective CRM and customer-based marketing strategies.
A V-Model software development application for sustainable and smart campus analytics domain
(2021) Doğan, Onur; Bitim, Semih; Hızıroğlu, Abdülkadir
As small cities, university campuses contain many opportunities for smart city applications to increase service quality and efficient use of public resources. Enabling technologies for Industry 4.0 play an important role in the goal of building a smart campus. An earlier work of the authors proposed a framework that was proposed for the development of a smart campus applications. It was the digital transformation process of İzmir Bakırçay University which is a newly established university in Turkey. This study is related to the final part of the developed framework. It aims to systematically develop a software for a sustainable and smart campus. V-model software development methodology was followed in the study. The methodology was applied for the corresponding stage which mainly includes real-time analytics, monitoring, reporting and performance management. The data flow diagrams were presented at three levels, a context diagram for a basic form of the system and parent diagram for the detailed software modules, and a child diagram for a selected module. This study can guide to the following researches to create a smart campus framework and a real-time analytics software.
Realising newspaper sales by using statistic methods
(Springer, 2021) Doğan, Onur; Gürcan, Ömer Faruk
Today, some newspapers have started to service online only. One of the reasons of this situation is competitiveness and increasing costs in press market. So newspaper sale planning requires adaptive scheduling and understanding customer behavior well. Estimating the right number of delivery is crucial. It is succeeded with expert knowledge supported with proper analysis and techniques. This study focuses on understanding newspaper sales amount by revealing critical variables and their importance on sales. This is a critical shortcoming especially for newspaper companies, which always try to reduce the number of sell outs and increase the number of return in the delivered newspapers offer companies financial benefits. In this study, it was analyzed that whether different weather conditions (sunny, cloudy or rainy) and days (weekday or weekend) are effective in daily newspaper sales for Ankara, İzmir and İstanbul. One-way Anova, Two-way Anova, t-test, Levene’s, Kolmogorov-Smirnov, and The Kruskal–Wallis tests were used. Sales data was collected from 71 vendors of a national press firm in three cities between 12 September–31 December 2018. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

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