Search results

In this study, it is analyzed the validity of the exchange rate pass-through (ERPT) effect and the effect of interest rate and output level on the inflation rate (IR) in Brazil, Russia, India, China and Turkey (BRIC-T) between the years 1995Q1 and 2022Q4.

The methods such as the panel unit root test developed by Westerlund (2012), the LM bootstrap panel cointegration test developed by Westerlund and Edgerton (2007), the common correlated effects (CCE) estimator developed by Pesaran (2006) and the augmented mean group (AMG) estimator developed by Eberhardt and Bond (2009) that take into account the cross-section dependency are applied for analysis.

As a result of the findings, it is determined that the ERPT effect is valid in Turkey, Brazil, Russia, India and China and the cost channel is valid only in China. Finally, it is found out that output level positively affects inflation in Turkey, Brazil, Russia, India and China.

All these results indicate that the economies of Turkey, Russia, Brazil and India have a fragile structure, especially in terms of inflation. Therefore, the central bank of these countries should maintain exchange-rate stability to implement the inflation-targeting strategy successfully. In this context, central bank independence should be increased in these countries in achieving this objective. Also the results indicate that it is still early to consider whether BRIC-T countries and accordingly the Belt and Road Initiative will be an alternative against the domination of the USA and European Union (EU) on international trade system or it will substitute them.

In this study, it is tested that the impact of interest-rate (NIR), exchange-rate (FER) and output level (IPI) on general level of prices. Besides, it is analyzed that whether production level affects the IR. Also, the study investigates the economic issues such as ERPT effect and cost channel. The study analyzes whether China's Belt and Road Initiative is successful or not. In this study, we used the panel data methods that allow for structural breaks and cross-section dependency. For these reasons, this study differs from other studies in the literature both in terms of scope and methods used.

In today’s economic conditions, businesses face great challenges related to competitiveness. The effort to respond flexibly to the changing business environment and customers’ demands constantly puts pressure on innovation. For this reason, research purpose to examine the effects of learning capabilities and market orientation in logistics companies during the pandemic.

In this research, a quantitative method was adopted and partial least squares structural equation modeling (PLS-SEM) was applied. The research is based on four variables. A conceptual research model was established through literature review and the model was tested. Within the scope of this research, A sample of 544 participants was taken to construct and test the model, and a 39-statement scale was presented to them. After presenting the reliability and validity values on the model, hypotheses were tested. Analyses were conducted using Smart-PLS 3.3 software.

As a result of the research conducted in logistics companies, the positive effects of learning orientation on performance outputs and the positive effects of market orientation as both a mediator and an independent variable show that these concepts are important for company management.

Considering the limitations of the research, it would be wrong to generalize the results of the analysis for different sectors because the data were collected from experts working in logistics companies. Therefore, it is necessary to make evaluations taking into account the limitations of the research. In future studies, it is recommended to make comparisons with research in different sectors, taking into account the limitations, and to enrich the literature with more research in this area.

Because of the importance of logistics activities seen in all countries with the pandemic period, it can be explained as a result of the analyses that the performance outputs are positively affected by the learning orientation, the companies’ adaptation to continuous change and development and their emphasis on market orientation at the same time.

The research is an original study as it analyzes the effects of learning orientations of logistics companies on the problems and opportunities experienced in the supply and distribution channel along with the pandemic process.

The research paper’s purpose is to contribute to the literature by analysing the essential resources and processes required for successful commercialisation, the contemporary challenges and opportunities of artificial intelligence initiatives in Türkiye, and the diverse models and methods employed by these initiatives.

Within the scope of the research, interviews were conducted with 10 entrepreneurs who established artificial intelligence-oriented enterprises in technoparks in Istanbul and Antalya. All 10 interviews were analysed using the MAXQDA20 software tool. Structured qualitative content analysis was used for the data analysis procedure.

Based on the research, external factors have a significant impact on the future growth opportunities of the market. Expanding the client base, gaining international recognition, and securing financing are crucial for success. However, the findings reveal challenges in the relatively young local ecosystem. One major criticism is the lack of support in marketing and sales activities for refined products. To address this, providing financial incentives and knowledge transfer to those in need is vital.

Since the research was conducted only with entrepreneurs who established and successfully commercialised artificial intelligence-oriented enterprises, it is recommended that future studies be performed with a widespread sample group, considering this limited situation. Furthermore, to overcome survivorship bias, it is recommended that posterior studies include failed commercialisation attempts in AI ventures.

It can be argued that there is no deliberate approach or model for commercialization. Entrepreneurs often draw from their own prior experiences or observe industry trends. Given the limited financial resources available in the domestic market and the challenge of attracting foreign investors to Turkish brands, entrepreneurs tend to rely on internal approaches for commercialisation.

This research delves into the commercialisation prospects and obstacles encountered by AI start-ups in Türkiye. It comprises qualitative insights into business models, commercialisation approaches, opportunities, and challenges. The data were obtained from interviews with entrepreneurs operating in the industry.

The main purpose of examining innovation development (ID), technology management (TM) and big data analytics capability (BDAC) from the perspective of information technology companies is to help these companies optimize their business strategies and increase their competitiveness. When these concepts are considered together, it is aimed to present suggestions that information technology companies can increase their innovation capacities, optimize their technology portfolios and develop their big data analytics capacities.

Data were collected from information technology companies working on big data analytics in technoparks in Istanbul. In the research, the Marmara region of Turkey was preferred because it is the region where the information technology sector is most common. In total, 503 questionnaires were collected. SmartPLS (4.0.8.4) licensed software was used in the research, and the results are presented with tables and figures.

As a result of the analysis of the data, it is supported by hypotheses that ID and TM have positive effects as independent variables and BDAC has positive effects as both independent and mediation variables.

In terms of the limitations of the research, since the data were collected only from the information technology companies in the technoparks in Istanbul, it would not be correct to generalize the analysis results. For this reason, it is recommended to develop a research model and contribute to the literature by considering this limited situation for similar studies to be conducted in the future.

By focusing on ID, it is important for companies to analyze their innovation processes and increase their ID capacity. On the subject of TM, analyses help companies identify their current technological infrastructure and development needs and optimize their technology portfolios. Big data analytics is an important tool that companies can use in their decision-making processes. Therefore, analyses of big data analytics can evaluate companies' current data analytics capacities and offer improvement suggestions.

So why are ID, TM and BDAC important? Why should a research model be developed to examine the effects of these variables? This situation can be understood by looking at the investments made by two world-class companies with headquarters in Istanbul/Turkey. L'Oréal Turkey integrates big data, cloud computing, artificial intelligence and digital platforms into its business processes by investing in new technologies and also makes a difference with innovation in environmental sustainability and social responsibility. PepsiCo, on the other hand, placed a great emphasis on innovation by opening its third Design and Innovation Center in Turkey and Europe in Istanbul. For this reason, examining the effects of ID, TM and big data analytics together in the research is important for the originality of the research. Examining these variables by focusing on their interactions and effects increases the originality of the subject.

The purpose of the article is to examine the concepts of knowledge management strategies, innovation and service quality in information technology companies that have research and development (R&D) departments in the technoparks of research universities.

The research was carried out in information technology companies with R&D departments in the technoparks of universities. Due to the “innovation” focus of the research, 302 engineers were selected by random sampling from engineers working in information technology companies in technoparks, and the prepared scale was sent to them via e-mail. In total, 302 units of data were subjected to path analysis and mediation effect analysis using the SmartPLS program.

In the research, it is supported by hypotheses that both knowledge management strategies and organizational innovation have a positive effect on the success of service quality and product innovation in information technology companies with R&D departments. At the same time, it can be explained as a result of analysis that innovation capability has both an independent and an intermediary variable effect.

Considering the limitations of the research, it is not correct to generalize the results of the analysis because the research was conducted only in information technology companies located in technoparks, and the data were collected from engineers working in these companies. For this reason, it is recommended that similar studies that are planned to be conducted in the future should do their research by taking this situation into account. At the same time, it is recommended to carry out future studies in different sectors and to bring the results obtained to the literature by comparing them.

The importance of information is increasing in technology-oriented companies where competition is increasing. Companies that cannot go beyond imitation or offer similar products and/or services cannot compete with their competitors in a competitive environment. The fact that companies can be successful in a competitive environment is supported by hypotheses as a result of the analysis that they need to develop organizational innovation and knowledge, as well as develop innovation capability at the same time.

The research is an original study in terms of examining the R&D departments of information technology companies operating in the technoparks of universities. Innovation and knowledge management strategies are examined within the scope of the research model by collecting data from information technology companies with R&D departments.

The purpose of this study is to understand how the level of readiness for artificial intelligence (AI) affects the overall performance of companies, determine the role of organizational flexibility in adapting to new technologies and business models and assess the importance of lean sustainability and value creation for technology-focused companies.

Technology companies working in technoparks in Istanbul were determined, and a questionnaire was applied to senior employees such as experts, engineers and managers working in these companies. The results were processed with a sample of 456 units. SmartPLS program was used for analysis.

As a result of the analyzes, it is supported by hypotheses that AI readiness and organizational flexibility have positive effects on lean sustainability and value creation.

When evaluated in terms of the limitations of the research, it would not be correct to evaluate the results of the analysis in general, since the data were collected from technology-focused companies in technoparks in Istanbul.

Examining the variables that make up the research model in technology-oriented companies helps to understand the critical factors for the future success of companies. At the same time, this research is important for companies to make more informed decisions in their strategic planning, technological transformation processes and value creation strategies.

This research topic offers a unique approach in terms of bringing together topics such as AI readiness, organizational flexibility, sustainability and value creation. These issues play an important role in the strategic planning of technology-focused companies, and when considered together, they are important in terms of examining the critical factors that affect the future success of companies.

In the extant literature, the concepts of charity and philanthropy have been differentiated based on the belief that charity stems from religious motivations and philanthropy is often secular in origin. Accordingly, this paper aims to investigate whether there is a distinction between managerial practices regarding the given concepts as emphasized in the conceptual discussions.

To see the managerial practices, the authors determined bazaars, community fundraising events organized by nonprofit organizations (NPOs), as the research field. Then, this study followed the general systematic of qualitative research. Accordingly, the authors conducted 44 interviews with experienced bazaar organizers from 10 NPOs in total. Furthermore, four days of participant observation with field notes were made in each bazaar, which lasted from 7 to 10 days. This study also used archival data as a secondary data source and then analyzed all data with a content analysis technique.

This study found that the field practices mainly do not support the distinction drawn over the conceptual discussions. Both concepts are nouns describing the act of giving and helping the needy. They are actively performed based on different motives (religion-based and secular).

The relevant distinction is limited to the conceptual discussions and has not been supported by the findings obtained from the field. Also, most of the studies on helping were carried out in the Western context. Studies conducted outside these cultures are quite limited. The value of the current study lies in the fact that it was conducted in a cultural context different from the Western cultures and paves the pathway for future research.

This paper aims to explore the numerical study of the steady two-dimensional MHD hybrid Cu-Fe₃O₄/EG nanofluid flows over an inclined porous plate with an inclined magnetic effect. Iron oxide (Fe₃O₄) and copper (Cu) are hybrid nanoparticles, with ethylene glycol as the base fluid. The effects of several physical characteristics, such as the inclination angle, magnetic parameter, thermal radiation, viscous propagation, heat absorption and convective heat transfer, are revealed by this exploration.

Temperature and velocity descriptions, along with the skin friction coefficient and Nusselt number, are studied to see how they change depending on the parameters. Using compatible similarity transformations, the controlling equations, including those describing the momentum and energy descriptions, are turned into a set of non-linear ordinary differential equations. The streamlined mathematical model is then solved numerically by using the shooting approach and the Runge–Kutta method up to the fourth order. The numerical findings of skin friction and Nusselt number are compared and discussed with prior published data by Nur Syahirah Wahid.

The graphical representation of the velocity and temperature profiles within the frontier is exhibited and discussed. The various output values related to skin friction and the Nusselt number are shown in the table.

The new results are compared to past research and discovered to agree significantly with those authors’ published works.

Emerging nations strive to diminish their ecological impact to meet net-zero targets, yet encounter formidable hurdles in curbing their environmental footprint. This purpose necessitated the study into impact of stock market, renewable energy and international investment on the ecological footprint in emerging countries from 1990 to 2020.

The study used augmented mean group (AMG) estimator, cointegration and heterogenous panel causality approach.

Results from the AMG show that renewable energy consumption reduces environmental pollution in most countries except Mexico. The study disclosed that stock market capitalization decreases ecological footprint in emerging countries. Using both the Kao and Pedroni cointegration methods, the study affirms the existence of stable equilibrium relationship in the long term. The causality test concluded a bidirectional relationship between stock market and ecological footprint and a unidirectional link between international investment, clean energy and ecological footprint.

The research is limited to only emerging countries. Therefore, future research should examine the environmental impacts of renewable energy consumption in different countries and regions, taking into account the local environmental conditions, policies and practices. This would help to identify the best practices and standards for minimizing the ecological footprint of renewable energy technologies and maximizing their benefits for environmental sustainability.

The study found that stock market capitalization reduces ecological footprint in Brazil, China, Turkey and India. To foster a culture of sustainability in stock market development impact, academic policies should emphasize the integration of environmental education across disciplines. By promoting awareness of the ecological consequences of stock market activities, societies can cultivate a mindset that values responsible economic practices. This, in turn, can lead to informed decision-making at individual and institutional levels.

First, since the study found that clean energy reduces ecological footprint, advocating for utilization of clean energy sources could be a key priority in emerging countries. Governments should incentivize the development and adoption of renewable energy technologies, such as wind and solar power, by providing subsidies and tax benefits. Furthermore, increasing awareness among residents about the benefits of clean energy and promoting its utilization in both residential and commercial environments can expedite the transition to a more environmentally friendly energy combination.

First, it pioneers an exploration into the interplay between stock market capitalization, international investment, clean energy and ecological footprint in emerging countries. Secondary unlike, unlike prior research, this study uses methodologies that account for cross-sectional dependencies and a unique characteristic specific to each country. In addition, by using common correlated effects mean group, AMG, cointegration and causality procedures, this study distinctly isolates and analyzes empirical findings for each country, leading to policy-oriented outcomes.

In this paper, we explore the impact of land management practices on post-disaster housing, to draw lessons from the case of reconstruction in Türkiye.

We conducted two qualitative case studies of two reconstruction experiences following the 2020 Elazığ and İzmir earthquakes. We analyzed 70 articles, technical reports and press releases and then used a set of policy analysis tools to examine five policy documents in depth. Finally, we wanted to understand how key officers interpreted these policy documents, so we closely analyzed the transcripts of eight semi-structured interviews.

Türkiye’s legal framework comprises five main policies that concentrate power in the central government and are not tailored to post-disaster reconstruction. This framework facilitates the construction of rubber-stamped apartment buildings, which disregard cultural and social contexts and practices. The current reconstruction policy neglects alternative options like cooperative housing, which could better respond to communal needs and expectations. It also often leads to the loss of land rights among affected residents.

We only analyzed decision-making processes in two case studies and based our study on a limited number of interviews. Therefore, it is difficult to generalize our results and apply them to other contexts. Further quantitative and qualitative work is necessary to conceptualize the links between land management and post-disaster housing reconstruction.

Our findings suggest a need for legislative frameworks specifically designed to address land management during post-disaster reconstruction. The concentration of power in central governments is problematic, thus it remains crucial to empower local authorities by reinforcing technical expertise and facilitating administrative autonomy.

This study offers unique insights into how power relations influence land management practices in post-disaster housing reconstruction. Examining the centralization of power and its impact on cultural and social practices identifies common forms of dispossession and points to key areas for policy improvement.