Journal of Information and Organizational Sciences

271-281

Authors: Xhelil Bekteshi, Sevdie Alshiqi

Kosovo’s private sector business is led by small and medium enterprises and shows a crucial role in the economic development and promoting the growth of this sector. Due to the lack of studies in Kosova, related to marketing strategy and export performance, the research aims to explore growth determinants of SMEs in Kosovo by emphasizing exports, revealing the importance of marketing strategy related to the performance of SMEs. Since exporting is becoming more important, it is necessary to understand all the factors that are involved in this booming trade. This research analyses explore the literature dealing with small and medium enterprises' performance to inspect the traditional and modern academic standpoints on estimating the impact of export performance, based on secondary data of five hundred small and medium enterprises, as trade, manufacturing, and services sectors in Kosovo. The data were analysed using both descriptive statistics and inferential techniques, such as logistic regression analysis, and probit model using the SPSS software. Results show a significant linkage of marketing strategy and export performance; managers and policymakers can take some action to improve export performance. On the other hand, the results measure the impact of price, production, promotion and place in export performance incorporate expected future performance. It is argued that enterprises in Kosovo must pay more attention to strategies, and attempt to design and implement better strategies that will be beneficial for developing international trade, especially exports, as one way of trading by SMEs.

305-331

Authors: Tamara Šmaguc, Ksenija Vuković

The paper examines traditional knowledge about the role of financial and physical resources in entrepreneurship. Based on Bourdieu's theory, we search for an answer to the question of which forms of economic capital are used by Croatian entrepreneurs in the computer programming industry and what their value in the context of accessing other forms of capital is. The study is based on a qualitative methodological approach. In-depth interview technique accompanied by unstructured observations was used in data collection. In addition to primary data, research includes the use of qualitative and quantitative secondary data. Research suggests that in the computer programming industry, economic capital is just one tool in the conversion game of entrepreneurial capital. Moreover, the interviewed entrepreneurs attach the least importance to it in business, favoring the value of intangible resources such as specialized knowledge, business connections and personal acquaintances. The company's start-up phase is characterized by the entrepreneur's reliance on personal savings, which is replaced by financing based on retained earnings in the later stages of business. Other forms of growth financing, such as bank loans and recapitalization of external investors, are used by a minority of larger companies, with a good base of symbolic capital. The results on capital conversions indicate relatively easy conversion of economic capital into cultural capital and symbolic capital, and less frequent use of economic capital to create social capital. Fresh insights into the entrepreneurs' perceptions provided by the study expand existing knowledge about entrepreneurship within the computer programming industry, suggesting that it is an industry with huge potential for young talents without a personal financial base that is commonly considered a precondition for entering entrepreneurship.

355-373

Authors: Norzaidi Mohd Daud

This study examines the impact of transformation in higher education, in particular on the introduction of new technology to students in Malaysia. This study is unique as it focuses on usage and technology resistance. Another uniqueness of the study is that technology resistance is measured by non-technology and post-technology antecedents, which have yet to be discovered by existing studies. These factors could potentially influence students to refrain from using technology in their studies, as many previous studies only focus on usage. Furthermore, prior research should have classified different types of resistance that cause significant knowledge gaps in technology education. A survey of 156 respondents concluded that antecedents of non-technology usage do lead to resistance. Post-technology usage, similarly, does influence resistance. As expected, the usage of technology influenced students' performances. Finally, resistance to technology did not affect students' performance. This is likely the first study to examine the impact of transformation in education and classify the antecedents of technology resistance into two categories: non-technology usage and post-technology usage. This research will help policymakers understand how students react to educational transformations. Adding technology could improve how well students do in university, but it could also hurt how well they do in university.

387-400

Authors: Tomáš Červinka

Strategic management of SMEs is perceived as crucial backbone of their business, as it impacts their business models and internal processes all the way up to digital innovation measured by the level of digital maturity. How do the strategic management factors influence the digital maturity? Through quantitative analysis of 76 respondents representing SMEs in the Czech Republic, the research data was collected and statistically tested. Results imply that strategic management factors affect the level of digital maturity. This paper contributes to prior literature by practical implementation of modified digital maturity model and by addressing the correlation of strategic management factors and the level of digital maturity. Limitations springing from sample site and environment are addressed and discussion on the results is conducted. Author proposes a conclusion that strategic management factors can be perceived as a driver of digital transformation, emphasizing the need for future research and practical discussion.

423-443

Authors: Amine El Hadi, Youness Madani, Rachid El Ayachi, Mohamed Erritali

Search engines are now the main source for information retrieval due to the huge expansion of data on the internet over the last ten years. Providing users with the most relevant results for their queries poses a significant challenge for search engines. Semantic search engines, which go beyond traditional keyword-based searches, have appeared as advanced information retrieval systems to address this problem. These search engines produce more precise and pertinent search results because they understand the meanings of words and their relationships. They play a pivotal role in managing the vast amount of internet data, with a primary aim of enhancing search precision and user satisfaction. However, improving search precision remains as an important goal for natural language processing researchers. The main objective of our research is to improve the search engine results. We present a novel approach for measuring the similarity between a user’s query and a list of documents within a search engine. This approach provides a new fuzzy recommendation system using a syntactic and semantic similarity. Our results indicate that our method outperforms several existing approaches from the literature, achieving a high level of accuracy.

473-490

Authors: Mawloud Mosbah

In this scholar, we compare three metrics for machine translation, from English to French and vice versa, and we give some combination formulas based on some schemes, algorithms, and machine learning tools. As an experimental dataset, we consider 10 English and French theses abstracts published in the web with four free in charge machine translation systems. Five combinations, with the same implicit weights, are considered namely: (BLEU+NIST), (BLEU+ (1-WER)), (NIST+(1-WER)), (BLEU+NIST+(1-WER)), and (FR(BLEU)+FR(NIST)+FR(WER)). These combinations are also considered differently through generating weights parameters on the basis of regression. The results of 12 formulas are computed and compared then in total. According to the obtained results, average regression combinations based on machine learning step are the best, especially with the three basic metrics, followed by average WER metric in the case of English to French. For French to English, (FR(BLEU)+FR(NIST)+FR(WER)) combination is the best followed respectively by the average regression combination with both first parameters (Reg(α,β)) and average BLEU basic metric. Another performance criterion is considered here, in the second position, namely: the number of times, over the 10 abstracts, where the formula is the best. Based on the obtained results, combination with regression based on the first and the last parameters (Reg(α,γ)) outperforms the others, in the case of English to French, with 3 times followed by Reg(β,γ), Reg(α,β,γ), NIST+(1-WER), and the basic metrics (BLEU, NIST, and WER) with 2 times for each of them. For French to English, the basic WER metric outperforms the others with three times followed by BLEU, (BLEU+ (1-WER)), (FR(BLEU)+FR(NIST)+FR(WER)), and Reg(α,γ) with 2 times for each of them. To note that there is a room of improvement for the combinations with1.0914 in the case of English to French and 1.01 in the case of French to English.