Mokslo publikacijos

The agricultural sector consumes energy in various forms while simultaneously generating agricultural waste and wastewater, and remaining a major contributor to carbon emissions. In line with the 3R principles—Reduce, Reuse, and Recycle—circular economy (CE) in agriculture has emerged as a key pathway toward achieving the Sustainable Development Goals (SDGs).

Against the backdrop of the profound adjustment of the global industrial structure and the rise of the Fourth Industrial Revolution, the contradiction between rapid economic growth and ecological environmental protection has become increasingly prominent. Promoting green development has become a key path to achieving sustainable urban development.

The European Green Deal, including the Farm to Fork and Biodiversity strategies, assumes an increase in the area under organic farming to 25% by 2030. In order to achieve this goal, it is important to understand the factors that lead to the development of organic farming.

The transition toward a circular economy (CE) in global manufacturing is hindered by challenges such as limited traceability, fragmented waste flows, and lack of compliance enforcement. Blockchain technology, with its capabilities in transparency, immutability, and decentralization, presents a promising solution to address these gaps. This study develops a decision-oriented framework to evaluate blockchain-enabled strategies for circular waste management. Drawing on expert insights collected through a Delphi process and applying the Best-Worst Method (BWM) and TOPSIS, the research prioritizes strategic alternatives based on key criteria including traceability, regulatory compliance, and ease of integration.

The dominance of quantitative research methods in business is evolving as modern market complexities demand a more comprehensive approach that integrates qualitative insights. This chapter presents the successful application of qualitative research in understanding experiential marketing strategies at the MACq 01 Hotel in Tasmania, Australia.

This study investigates the evolution of customer-centric innovations within modern business ecosystems through the lens of servitization, a concept gaining momentum in contemporary service delivery frameworks. Recognizing the limited exploration of servitization beyond anufacturing, particularly in the context of value-added services, this research employs a multiple ase study methodology focused on the tea sector in India and Nepal.

The purpose of this research is to provide an evaluation of sustainable agricultural development in the Baltic countries (Lithuania, Latvia, and Estonia), with contextual references to EU sustainability frameworks such as the Green Deal and Common Agricultural Policy.

The integration of Industry 4.0 and Artificial Intelligence (AI) technologies has redefined global supply chain operations, with increasing emphasis on sustainability as a strategic priority. Despite this evolution, there remains a significant gap in the literature regarding the structured prioritization of sustainability-related indicators influenced by digital transformation.

The present paper is the first scientific investigation of the future European farmer profiles. An expert interview combined with sophisticated multi-criteria decision-making techniques were employed as main research tools. Lithuania served as an empirical basis for the research. The dynamics of the development of the share of future European farmer profiles in 2023 and 2040 is assessed. The resilience index for the calculation of the agricultural economic resilience level for the each of the future European farmer profiles is created

This study examines the impacts of macroeconomic indicators, such as exchange rate, interest rate, money supply, and inflation, on the stock index of Pakistan (PSX), India (BSE), and China (SSE). The researchers have taken monthly data from Jul 2001 to March 2023 and employed a Nonlinear Autoregressive Distributed Lag (NARDL) approach to investigate the asymmetric effects of the variables. The Bound test result for the cointegration relationship demonstrated a long-run relationship (or cointegration) between LPSX, LSSE, and macroeconomic variables.