Trenevska Blagoeva, Kalina

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Trenevska Blagoeva, Kalina

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BIG DATA ADOPTION IN SELECTED COMPANIES OF THE RETAIL SECTOR IN THE REPUBLIC OF MACEDONIA
(INSTITUTE OF KNOWLEDGE MANAGEMENT SKOPJE, MACEDONIA, 2018-12-10)
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In a highly digitalized world, big data and analytics are among major trends companies worldwide are facing. As companies generate data across different sources (information systems), which is increasing rapidly in volume, variety and velocity, big data analytics becomes essential. Big data is a term that describes the large volume of data (both structured and unstructured), that overwhelms a business on a day-to-day basis. But the importance of big data doesn’t revolve around how much data one organization has, but what organizations do with the data that matters. Big data and analytics, provide organizations with the opportunity to analyze data generated from any source and to find answers that enable cost reductions, time reductions, new product development and optimized offerings, and smart decision making. Big data is affecting companies from different size and in almost every industry, and has the potential not only to transform the business world, but the society as well at large extent. Emerging literature and the empirical evidence suggest that companies from the retail sector can gain competitive advantage from data if they adopt big data analytics technologies. In spite of that, companies in the country are still in the early stages of adoption ofbig data analytics technologies. Hence, the goal of this paper is to determine factors affecting the big data analytics adoption in selected companies in the Republic of Macedonia from the retail sector. This is a pilot study and as such represents the first attempt to assess the level of big data analytics adoption in the country. This small scale preliminary study will provide evaluation of the feasibility of the key steps of the proposed research model (methodology) in order to conduct future research in larger extent and sample. There have been several theoretical models that explain technology acceptance. The research model in this study is based on Technology-Organization-Environment (TOE) framework (Tornatzky & Fleischer, 1990). The TOE framework explains that adoption of technological innovations is influenced by a range of factors in the context of the technology, organization and external environment. The framework explains that these three factors stimulate and influence the technology innovation adoption-decision in companies. It is considered as multi-perspective framework and an integrative model that is developed for studying factors affecting adoption of innovative technologies and has been used to assess organizations’ adoption of big data analytics technologies mostly in telecommunications, e-commerce and other. The proposed research model specifies the following technological characteristics (technical capacity, relative advantage and complexity), intra-organizational factors (top management support, organizational culture, organizational size and IT expertise/ technological competence), and inter-organizational factors (competitive pressure, external support, and regulatory /government policy as well as data security and privacy) as determinants of big data analytics adoption.The preliminary results of this pilot study support the research model and the methodology. The significance of the proposed determinants/factors can help managers formulate their analytics strategies and increase the use of big data technology in order to fulfill organizational goals and achieve better organizational performance
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Predicting consumer intention to use mobile banking services in North Macedonia
(M-Sphere, 2019-10)
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Smartphones and mobile technologies are becoming increasingly available and affordable in the Republic of North Macedonia. Followed by this trend, many banks are providing banking services to customers via smartphones. They are increasingly investing in mobile channels by providing new mobile banking services. The penetration rate of smartphones is increasing globally and smartphones are the most used devices for access to the Internet in the country i.e. by 81% of Internet users in 2018, and mostly among persons aged 15-24 (91.8%) (State Statistical Office, 2019). Therefore, the goal of this research is to examine predictors of consumer intention to use mobile banking services in North Macedonia. In order to get insights regarding the user adoption of m-banking services in the country, a survey was conducted during April 2019 among more than 150 mobile users. The research model proposed in this study examines the influence of several basic constructs that explain technology acceptance and innovation diffusion. In addition, its originality and practical implications is reflected in determining the significance of additional constructs that are specific for the m-banking domain, such as social image and bank’s reputation. The results of the empirical study are supporting the proposed basic constructs of the model and some specific relationships are unveiled. By highlighting the usefulness of integrating constructs from different theories of technology acceptance, this research is a holistic approach representing a solid base for future studies on the adoption of new technologies in the country. From practitioner’s viewpoint, this research offers valuable insights for developing m-banking solutions.
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EVALUATING DATA ANALYTICS ADOPTION IN SELECTED COMPANIES OF THE FINANCIAL SECTOR IN THE REPUBLIC OF NORTH MACEDONIA
(Faculty of economics - Prilep, St.Kliment Ohridski University, Bitola, Republic of North Macedonia, 2019-10-19)
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Data analytics has become one of the driving forces for digital transformation efforts of companies around the world (Keary, 2019). Nowadays, in a highly digitized environment, companies generate data across different sources which is increasing rapidly in volume, variety and velocity. There is no doubt that companies can use these datasets for creating a more efficient services that deliver a more targeted customer experience. Hence, the importance of data analytics has become essential for organizations to find new opportunities and gain new insights to run their business efficiently. Emerging literature and the empirical evidence suggest that companies from the financial services sector have a lot to gain by adopting data analytics (minimize risks, detect fraud, improve credit risk management, improve marketing activities in real time etc.). In spite of that, companies in the country are still in the early stages of adoption of data analytics technologies. This research is a pilot study and represents the first attempt to assess the data analytics adoption maturity in selected companies of the financial sector in the country. The methodology used in this research for evaluating data analytics adoption is based on Maturity Model for Data and Analytics (IT Score for Data and Analytics) (Gartner, 2017), since it best describes maturity levels in service sectors. The assessment is founded on interviewing managers using questionnaire that guides respondents through all dimensions and levels proposed by the model. In the model four measurement areas are analyzed: Strategy, People, Governance and Technology. For each area, five maturity levels are defined: Basic, Opportunistic, Systematic, Differentiating and Transformational. Survey results confirmed that analyzed companies fully understand the benefits of data and analytics as valuable source to gain competitive advantage from data and the overall level of data and analytics maturity is set on level 2 for almost all dimensions.
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Applying TAM to Study Online Shopping Adoption Among Youth in the Republic of Macedonia
(University of Primorska, Faculty of Management, Slovenia, Lomonosov Moscow State University, Moscow School of Economics, Russian Federation Juraj Dobrila University of Pula, Faculty of Economics and Tourism, Croatia Association for the Study of East European Economies and Cultures, USA Society for the Study of Emerging Markets, USA, 2017-05)
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The purpose of the paper is to analyze factors that determine online shopping adoption among young people in the Republic of Macedonia. Online shopping is gaining popularity especially among youth in the Republic of Macedonia. It has been recognized in general that youth are strongly representative sample of today’s online population. This especially counts to online shoppers in our country. The proposed research framework is TAM based, extended with relevant constructs that are essential for online shopping– trust, website usability and customer service. They are particularly relevant determinants for the Republic of Macedonia having in mind the size of the market, underdeveloped delivery channels, and inability to use online payment, customs barriers etc. as predominant factors that can influence consumers final decision to shop online. Significance of the factors included in our extended TAM model is tested using regression analysis. From the results, all investigated factors are proven to be significant. For further research, moderating effects of demographic factors can be investigated as may contribute to deeper understanding of consumers’ attitudinal intention to shop online. Also, computer anxiety and web irritation can be observed as factors influencing behavior of online shoppers.
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Adoption of electronic public services: the case of the Republic of Macedonia
(Faculty of economics and business, University of Zagreb, Croatia, 2016-06)
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Abstract: This paper identifies the factors that determine users’ adoption of e-Government services in the Republic of Macedonia. The research model, which is based on the Technology Acceptance Model, defines several constructs (perceived ease of use, perceived usefulness, compatibility, interpersonal influence, external influence, self-efficacy, facilitating conditions, attitude, subjective norms, perceived behavioral control, demographic factors) that can influence intention to use e-government services. Relationships between constructs proved to be significant after analysis of the survey results. The intention to use electronic public services is influenced by the attitude and subjective norms, while perceived behavioral control was not significant for our sample.
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Determinants of Online Shopping Behaviour of Young People in the Republic of Macedonia
(Faculty of economics and business, University of Zagreb, Zagreb, Croatia, 2018-05)
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The main purpose of the research is to analyze the significance of determinants of young people’s online shopping behaviour in the Republic of Macedonia. The research was conducted among more than 355 students (graduate and postgraduate) using structured questionnaire (both online and offline) including demographic characteristics of the respondents and their online behaviour measured by time spend online, devices predominantly used to connect to internet and frequently visited sites for online shopping. In addition, questions concerning their preferences for types of goods that are bought online are included in the questionnaire. Online shopping is gaining popularity especially among youth in the Republic of Macedonia. It has been recognized that youth are strongly representative sample of today’s online population in our country. The research model is based on Unified Theory of Acceptance and Use of Technology (UTAUT) model which provides a framework for explaining and predicting technology use behaviour, in our case online shopping behaviour. Original constructs that were included are: performance expectancy; effort expectancy; social influence; facilitating conditions and behavioural intention toward using technology. As extensions of the original model, we added three more constructs proposed by UTAUT2 model – hedonic motivation, price value and habit that are proven to be determinants of online behaviour. The results showed that all predicted relationships are proved to be significant. From the regression analysis and the proved relationships between constructs we can conclude that UTAUT2 model is good representation of real determinants that influence online shopping behaviour among young people in the Republic of Macedonia. This research represents pilot study in this field in the country and in the region. Hence it could be used as a good base for further research in this scientific area and as a guideline for e-commerce managers and marketers to improve shopping experience and customer service.
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Determinants of mobile internet usage and opportunities for m-marketing among youth in the Republic of Macedonia
(Accent and M-SPHERE ASSOCIATION FOR PROMOTION OF MULTIDISCIPLINARITY IN SCIENCE AND BUSINESS, Zagreb, Croatia., 2017)
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The number of mobile Internet users is growing rapidly worldwide and the use of mobile Internet is changing consumer behaviour. Therefore, companies are extending their marketing opportunities and reaching their audience via mobile devices. Mobile marketing is gaining popularity in the last couple of years, due to the possibilities offered by new technologies embedded in smart phones. There have been several theoretical models that explain technology acceptance. Building on the extensions on UTAUT, consumer use and acceptance of technology led to UTAUT2 model. The aim of the research is to connect use of mobile Internet among young people in the Republic of Macedonia and opportunities of mobile marketing. The penetration rate of smart phones is increasing globally and in the last trimester of 2015 more than 72% of the Internet users in the country used smart phones to access the Internet (DSZ, 2015). The survey was conducted in April /May 2016 among more than 300 young people. Original UTAUT2 model is proposed to examine the influence of several constructs that influence use behaviour (performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit). The factors are explained in the context of the research and attention is paid on habit, hedonic motivation and price value as predictors of the mobile Internet usage. The results of the empirical study are fully supporting the model. Namely, all relationships hypothesized in the model are proved to be significant in our sample. However, the moderators such as age, gender and experience used in the original UTAUT2 model were not included, but are expected to be influential when analysed in larger and more representative sample. The significance of the proposed predictors can help managers formulate their marketing strategies and profound their marketing communication efforts.
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Assessing Organisational Maturity in Predictive Analytics of Telecommunications Companies in the Republic of Macedonia
(Economic analysis, Journal, INSTITUTE OF ECONOMIC SCIENCES, Belgrade, Serbia, 2019-06-24)
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Data analytics and predictive analytics are among major trends companies are facing worldwide. In a highly digitalised environment, it is not only to question the usage of data analytics but how analytically mature organisations are. The goal of this paper is to assess organisational maturity in predictive analytics of telecommunications companies in the country. In order to assess the level of organisational maturity in predictive analytics, we use Predictive Analytics Maturity Framework Assessment (PAMFA) (Capgemini, 2012), since it best describes maturity levels in the telecommunications sector. The method of analysis is based on interviewing managers with a questionnaire that guides respondents through all dimensions and levels proposed by the framework. According to the PAMFA five dimensions are analysed (Vision and strategy, Enablers, Competence, Deployment and Governance). For each dimension, four maturity levels are defined: Level 1: Impromptu, Level 2: Solo, Level 3: Ensemble and Level 4: Symphony (Capgemini, 2012). Survey results confirmed that analysed companies fully understand the benefits of predictive analytics as a valuable source of gaining competitive advantage from data. The overall level of predictive analytics maturity is set between levels 2 or 3 for almost all dimensions. This research is the first attempt to analyse organisational maturity in predictive analytics in the country. Its originality derives from the specific characteristics and development of the telecommunications sector. This sector is one of the most advanced service sectors in the country and hence represents a benchmark concerning digital transformation. Results of this survey provide useful information needed to design a roadmap for migrating towards higher maturity levels
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ASSESSMENT OF WEBSITES QUALITY OF THE MINISTRIES OF THE REPUBLIC OF MACEDONIA
(INSTITUTE OF KNOWLEDGE MANAGEMENT SKOPJE, MACEDONIA, 2018-09-25)
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By using e-government websites, all stakeholders can receive benefits. Citizens can receive better and more convenient services, businesses can reduce their cost while dealing with institutions and governments can reduce operation and management costs. For more than two decades, governments around the world are making their services available online via e-government websites. However, there are determinants that influence whether constituents will embrace the use of e-government websites. The explored factors are based on information and system-quality aspects since the existing works indicate these quality aspects affect the use and user satisfaction. This study, primarily explores the factors that influence the adoption of e-government websites of all fifteen Ministries of the Republic of Macedonia.The research is performed using structured questionnaire that consists of several parts. The quality of the e-government websites was assessed by 6 parameters of the official websites and the binary choice of the answers on the chosen statements (I agree/ I don’t agree). Graduate students were trained to perform the analysis by checking the ministries’ websites.The first determinant is Information qualitythat was assessed by 4 statements. The second determinant of quality is Information content parametersassessed by 5 statements. The third quality factor concerning e-government websites that is analyzed is Accessibility/ Navigation.The Usability/ Functionality/ Interactivity features are considered to be the most important for achieving higher levels of the e-government websites sophistication. Efficiencyand Security/Barrierswere also assessed. From the analyses of the received questionnaires several conclusions can be made. Without doubt, information quality is perceived as satisfactory from all respondents. They agree that on all websites of the ministries information are accurate, on-time, relevant and precise. Concerning the second determinant –information content, the answers are mainly in line with the statements except the fact that on most of the sites there is no FAQs. The accessibility/navigation characteristics are viewed as satisfactory, except keyword search. The forth group of characteristics is assessed by 10 statements that reflect usability, functionality and interactivity. The resultsare more variable across the answers. Discussion forums for citizens and businesses are not present and online tracking of proposals is not possible. Transactions online are not available as feature. All ministries are present on social media. However, most of the respondents answered negatively when they were asked about the security. As an overall conclusion we can stress out that quality of the websites of the ministries of the Government of the Republic is satisfactory from the information quality and content, while parameters of quality such as interactivity and functionality are perceived as less satisfactory. Websites don’t follow the same pattern, they are developed without compulsory functionalities and we can’t find consistency in the solutions. However, the progress is obvious in the perception of the transparency, open data, information content and connectivity with the social media. Still, two-way interactions are not possible and that is the step that will be hard to achieve without improving the security and interoperability.
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DETERMINANTS OF DATE ANALYTICS MODELS TO IMPROVE CUSTOMER ENGAGEMENT
(INSTITUTE OF KNOWLEDGE MANAGEMENT SKOPJE, MACEDONIA, 2018-03)
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Abstract: Organizations that turn data into insights are gaining competitive advantage through improved connections with consumers. Data analytics (DA) is the process of examining data sets in order to draw conclusions about the information they contain, aided by specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses. Our findings demonstrate a significant increase in the number of organizations that are using analytics to gain a competitive advantage and innovate — a key component of this shift is more effective use of analytics to improve customer engagement. Data and analytics allow organizations to use intelligence from feedback to tailor offerings that improve customer satisfaction. Several factors appear to be at work, including the use of a wide range of data sources, well-developed core analytics capabilities, and integration of artificial intelligence (AI) and the internet of things (IoT) into processes. Companies that have businesses as their main customers (business-to-business, or B2B) are gaining the most benefits from this shift, in part because they are able to share data with customers in a way that directly strengthens their relationship. Data analytics initiatives support a wide variety of business uses. For example, banks and credit card companies analyze withdrawal and spending patterns to prevent fraud and identity theft. E-commerce companies and marketing services providers do clickstream analysis to identify website visitors who are more likely to buy a particular product or service based on navigation and page-viewing patterns. Mobile network operators examine customer data to forecast churn so they can take steps to prevent defections to business rivals; to boost customer relationship management efforts, they and other companies also engage in CRM analytics to segment customers for marketing campaigns and equip call center workers with up-to-date information about callers. We assigned respondents to one of three categories based on their relative level of sophistication in adopting analytics: the Analytically Challenged organizations display limited analytical capabilities; Analytical Practitioners largely use analytics to track and support performance indicators; and Analytical Innovators incorporate analytics into virtually every aspect of their strategic decision making, including gleaning data from a variety of sources such as direct measurement and sensors, industry data, and third parties. One of the clear differences between Analytical Innovators and the other maturity groups is their ability to successfully use data and analytics to deepen customer engagement along several key dimensions. The most analytically mature organizations are twice as likely to report strong customer engagement compared with the least analytically mature organizations. According to this interpretation, Analytical Innovators’ heightened awareness of customer and competitor behavior leads to a greater appreciation of the risks of customer loss as a result of their data-driven customer intelligence and engagement. To determine the relative analytics proficiency of an organization, we calculated the Analytics Core Index, based on the organization’s core analytics capabilities in (1) ingesting data (capturing, aggregating, and integrating data); (2) analyzing (descriptive analytics, predictive analytics, and prescriptive analytics); and (3) applying insights (disseminating data insights and incorporating insights into automated processes).

Trenevska Blagoeva, Kalina

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