Effective Management Process Research Articles

Transparent and Mechanically Robust Janus Nanofiber Membranes for Open Wound Healing and Monitoring.

The electrospun nanofiber membrane has demonstrated great potential for wound management due to its porous structure, large surface area, mechanical strength, and barrier properties. However, there is a need to develop transparent bioactive nanofibers with strong mechanical properties to facilitate the monitoring of the healing process. In this study, we present an electrospinning-based method for creating transparent (∼80-90%), strong (∼11-13 MPa), and Janus nanofiber membranes. The innovative square pattern architecture of the membrane includes a thin hydrophobic polycaprolactone layer on top of a layer of hydrophilic ethylene-vinyl alcohol nanofiber, which enables the absorption of excess biofluid from the wound and exhibits Janus wettability for water. Furthermore, incorporating 5% chitosan into the composition of the nanofibers accelerates the healing process through its antioxidant properties and antimicrobial activity against various bacteria, including drug-resistant strains. The developed membrane also demonstrates skin-repairing function, quick blood clotting (around 145 ± 12 s), and biocompatibility with keratinocyte (≥90%), as well as in vitro quick cell migration (∼24 h). With a tensile strength of 11-13 MPa, the membrane effectively adheres to the knee joint even after running 4 km. These optimal properties of the electrospun nanofiber membrane make it suitable for effective wound management and inspection of the healing process, without the need for frequent dressing changes.

Microbial communities and their role in enhancing hemp fiber quality through field retting.

The current development of industrial hemp "Cannabis Sativa L." fibers for technical textiles and industrial applications requires high-quality fibers with homogeneous properties. However, several factors have been reported to influence the fibers' intrinsic properties, including a post-harvest process known as retting. This process plays a crucial role in facilitating the mechanical extraction of fibers from hemp stems. Retting involves the degradation of the amorphous components surrounding the fiber bundles enabling their decohesion from stems. Microorganisms play a central role in mediating this bioprocess. During retting, they colonize the stems' surface. Therefore, the biochemical components of plant cell wall, acting as natural binding between fibers, undergo a breakdown through the production of microbial enzymes. Although its critical role, farmers often rely on empirical retting practices, and considering various biotic and abiotic factors, resulting in fibers with heterogenous properties. These factors limit the industrial applications of hemp fibers due to their inconsistent properties. Thus, the purpose of this review is to enhance our comprehension of how retting influences the dynamics of microbial communities and, consequently, the evolution of the biochemical properties of hemp stems throughout this process. Better understanding of retting is crucial for effective process management, leading to high-value fibers. KEY POINTS: • Retting enables degradation of cell wall components, controlling fiber properties. • Microbial enzymatic activity is crucial for successful decohesion of fiber bundles. • Understanding retting mechanisms is essential for consistent fiber production.

Innovation and infrastructure: driving forces for entrepreneurship development and economic opportunities

Purpose. To determine the relationship between innovation and infrastructure to support entrepreneurship as factors of growth of economic opportunities, based on the results of empirical research. Methodology. The case method and modern tools of econometric research were used to create an economic-mathematical model that assesses the relationship between economic opportunities and indicators of economic innovation. The research is based on the results of the Gallup 75 Years Anniversary Survey on current and future economic opportunities, as well as Global Innovation Index (GII) indicators. Findings. Creating favorable conditions for doing business and developing entrepreneurship is critically important for the economic recovery of Ukraine. The high level of entrepreneurial activity among Ukrainians emphasizes the importance of the development of innovative infrastructure and business support. The developed models can be used to forecast the economic capabilities of the population, which will contribute to the return of citizens and the development of the national economy. Thus, innovations and an effective infrastructure to support entrepreneurship play a key role in ensuring sustainable economic growth and social well-being in Ukraine. The results of the study can become the basis for developing strategies for economic development and solving migration problems in the post-war period. Determinants of the growth of economic opportunities of the population (human capital) are determined. The suggested GII parameters most correlate to positive feedback on economic opportunities and growth over the next 25 years. Originality. For the first time, the relationship between economic opportunities, the development of innovations and the development of infrastructure at the enterprise has been empirically proven. Statistically significant predictors of current and future economic opportunities of the population are substantiated and relevant economic and mathematical models for their evaluation and forecasting are developed. Practical value. The results of the study are particularly relevant in the context of solving the migration crisis caused by Russia’s military aggression against Ukraine. The return of citizens who have left the country depends on the creation of favorable conditions for business and the development of entrepreneurship. The developed models can be used to forecast the economic opportunities of the population in different countries, which will allow effective management of migration processes and promote the development of national economies. This will ensure the creation of a favorable business environment, which is critical for sustainable economic growth and social well-being.

Designing the public works values

What are public works, and under what conditions can they be considered a “common value” recognized by the community? The contributions to issue n. 28 of TECHNE Journal delve into these conditions, offering critical reflections and research advancements that examine cities, buildings, places, and public services from the perspective that «the entire urban space must be regarded as something produced, owned, and transformed collectively» (Marella, 2024). There are three main areas of reflection and proposal: the first involves the methods and procedural and design tools that can be employed for the recovery and adaptive reuse of public works facing functional obsolescence, abandonment, and/or decay; the second addresses the regenerative processes of public spaces and entire urban sectors with a focus on usability and environmental sustainability; and the third concerns the participatory design of public works as a vital lever for the creation of social value. This set of design actions is well-supported by analytical and evaluative tools that guide the decision-making process, all driven by an interest in optimizing the socio-economic, cultural, and environmental benefits that can result from more effective and efficient public works production and management processes, especially in response to evolving social demands.

Examining trade strategies in Europe and Ukraine: Navigating challenges and building economic strength

Today, the global community operates within an integrated global economic system. Against the backdrop of globalised integration of the socio-economic sphere, international trade is positioned as a significant factor in the intensification of economic development. In this context, trade strategies can create new opportunities or risks for the national economy. This article aims to conduct a comparative analysis of the trade strategies of the European Union (EU) and Ukraine in the context of potential advantages and related challenges for economic resilience. The study finds that international trade helps to mitigate the limitations of national resource potential and the narrowness of the domestic market, intensifies the potential for innovative industrialisation, and accelerates economic growth. The specifics of forming the modern concept of international trade development in the context of the European community and Ukraine are identified. The main principles of modern trade strategies are considered, their strengths and weaknesses are analysed, and directions for improvement are highlighted. The impact of trade strategies on the level of economic resilience is examined. It is substantiated that a high level of competition in the global market requires the adaptability of producers’ trade strategies and the formation of appropriate structures to coordinate the functioning of the external economic relations infrastructure complex. The main success factors of a trading strategy when entering new markets are highlighted, including preliminary research of local legislation requirements and market dynamics, the development of adaptive marketing strategies, and effective management of customs processes. Active participation in the international trade environment has proven to open additional opportunities for realising economic potential. At the same time, it is necessary to specify the development strategy to ensure long-term competitive advantages.

Modern information technologies for studying the cost of working time as an important tool for effective management of business processes

Relevance. In the context of economic, social and socio-political changes, growth and increased competition, it is becoming increasingly interesting to study the issues of scientific organization and labor rationing, as well as factors affecting labor productivity, and, ultimately, the effectiveness and profitability of production processes in general. There is an objective need to improve not only the methods of managing the cost of working time, but also to skillfully apply modern digital technologies. That is why it is so important to develop and modify, in accordance with the requirements of the market environment, methods, tools and methods of analysis using artificial intelligence (AI) when studying the cost of working time of employees of an organization.The purpose is based on the study of theoretical and methodological approaches to improving the system of organization and rationing of labor, to provide a scientific justification for the relevance of the development of the processes of accounting for working hours of employees of the organization through the integration of modern information technologies.Objectives: to analyze the existing approaches to the organization and rationing of labor; to identify the potential of integrating modern information technologies into the processes of working time accounting; to develop practical recommendations for improving the system of accounting for the working hours of employees of the organization using modern information technologies.Methodology. The theoretical and practical basis for the study of modern approaches to the modernization of the system of organization and rationing of labor at the enterprise were the methods of analyzing literary sources, statistical data, expert assessments, as well as using an integrated approach.Results. The result of the research in the work is a comprehensive analysis of the use of artificial intelligence (AI) in studying the cost of working time to modify the processes of rationing labor functions through the integration of information technologies.Conclusions. In the course of the study, we proved the positive effect of the introduction of modern information technology systems at the enterprise, as well as scientifically substantiated the relevance of the development of processes for analyzing the cost of working time and rationing employees of enterprises through the integration of modern information technologies.

FEATURES AND IMPORTANCE OF BUSINESS PROCESSES IN ENERGY-PRODUCING ORGANIZATIONS

The article is devoted to the features and importance of business processes in energy-producing organizations. In the context of globalization and sustainable development, effective business process management is becoming a key factor in competitiveness. The article analyzes the main types of business processes in the energy sector, including production, distribution and service processes. Optimization methods such as automation and the introduction of innovative technologies that contribute to efficiency and cost reduction are considered. In addition, the importance of integrating sustainable practices and compliance with environmental standards is emphasized. In conclusion, the authors note that effective business processes are the basis for achieving strategic goals and sustainable development of energy-producing organizations.

SCENOGRAPHY DESIGN IN A DIRECTOR’S ARTISTIC PRACTICE

The paper describes a methodology of designing scenography for a contemporary theatrical performance in the academic process. The systematic approach to artistic visualisation of a performance, modernisation of its structure, selection of scenography functions, style and type of design widen the range of the director’s interaction with the audience as well as contributes to effective management of the creative process from the stage of the artistic concept design through to its implementation. The method of depicting compositional schemes to design action development helps individual types of art interweave with the director’s concept, develop creative thinking and cope with numerous management challenges. Designing diverse parts of staging paves the way to developing students’ skills of comprehending the processes of integration of arts and technologies. The “directing scenographic concept” method contributes to the integration of the director’s and the artist’s professional activities, helps to express a creative idea in a groundbreaking form, and turns into an effective tool of innovative design and management of a theatrical performance.

FORECASTING AND OPTIMIZATION OF CATALYTIC CRACKING UNIT OPERATION UNDER CONDITIONS OF FUZZY INFORMATION

This paper discusses the application of nonlinear regression to forecast and optimize the operation of catalytic cracking units under conditions of fuzzy information. Catalytic cracking is a crucial process in oil refining that produces high-quality gasoline and other light hydrocarbon products. However, the complexity of the process and the uncertainty of initial data complicate the modeling and optimization of plant operations. To address this issue, a nonlinear regression method is proposed that accommodates the fuzziness of input and output parameters described by linguistic variables. The methodology includes the collection and formalization of expert knowledge, the construction of fuzzy models, and their integration into the process control system. Forecasting is performed by creating regression models that describe the relationships between operational parameters and product quality characteristics. The paper presents a procedure for developing and applying nonlinear regression models, describes algorithms for synthesizing linguistic models, and provides examples of their use to optimize the operation of catalytic cracking units. The modeling results demonstrate the high adequacy and accuracy of the proposed method, as well as its advantages over traditional approaches in conditions of uncertainty and data scarcity. The scientific novelty of the research lies in the development and testing of advanced nonlinear regression models adapted for analyzing and optimizing catalytic cracking processes based on fuzzy data. These methods take into account the specificity and uncertainty of process data, improving the accuracy and reliability of forecasts, which facilitates more effective management of production processes in the petrochemical industry. The main reason for conducting this study is the need to improve the control of oil refining processes, particularly catalytic cracking, which plays an important role in producing high-quality gasoline. The complexity of this process and the presence of fuzzy information caused by fuzzy initial data require the development of new modeling and optimization methods. Existing traditional models based on deterministic methods are often insufficient under uncertainty. This leads to a decrease in the accuracy of process control, which can negatively affect the quality of the final product and production efficiency. The use of nonlinear regression in combination with fuzzy logic is a more flexible and adaptive approach that allows you to take into account the fuzziness and uncertainty of data and use expert knowledge to build models that match the actual operating conditions of the units. Thus, this study aims to solve the key problems associated with data uncertainty and the complexity of the catalytic cracking process, which will improve the accuracy of forecasting and optimization of the units. The main contribution is creating a model that uses nonlinear regression methods in combination with fuzzy logic. This allows uncertainty in input data (such as reactor temperature or pressure) to be effectively considered and processed to improve gasoline and other product yield forecasts. It is shown that using nonlinear regression combined with fuzzy logic significantly improves the management of technological processes, increases the output and quality of products, and reduces production costs. The conclusion of the paper discusses the prospects for further development of the methodology and its application to solve similar tasks in other areas of chemical technology.

Interactions of Saccharomyces cerevisiae and Lactiplantibacillus plantarum Isolated from Light-Flavor Jiupei at Various Fermentation Temperatures.

Chinese Baijiu is a famous fermented alcoholic beverage in China. Interactions between key microorganisms, i.e., Saccharomyces cerevisiae and Lactiplantibacillus plantarum, have recently been reported at specific temperatures. However, empirical evidence of their interactions at various temperatures during fermentation is lacking. The results of this study demonstrated that S. cerevisiae significantly suppressed the viability and lactic acid yield of L. plantarum when they were cocultured above 15 °C. On the other hand, L. plantarum had no pronounced effect on the growth and ethanol yield of S. cerevisiae in coculture systems. S. cerevisiae was the main reducing sugar consumer. Inhibition of lactic acid production was also observed when elevated cell density of L. plantarum was introduced into the coculture system. A proteomic analysis indicated that the enzymes involved in glycolysis, lactate dehydrogenase, and proteins related to phosphoribosyl diphosphate, ribosome, and aminoacyl-tRNA biosynthesis in L. plantarum were less abundant in the coculture system. Collectively, our data demonstrated the antagonistic effect of S. cerevisiae on L. plantarum and provided insights for effective process management in light-flavor Baijiu fermentation.

Selecting the Suitable Landfill Location for Efficient Waste Management in Udham Singh Nagar District, Uttarakhand: A Geospatial and Multi-Criteria Approach

The effective management process of solid waste is a pressing concern in Udham Singh Nagar district, where approximately 245 metric tons of waste is generated daily. To address this issue, it is essential to identify suitable landfill sites. This research aims to identify optimal sites for waste disposal in the district by combining the capabilities of Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) techniques. A total of ten key factors were evaluated and prioritized according to their respective significance. A comprehensive analysis was conducted using theses parameters, including distance from road networks, rivers, railroads, sensitive area, geology, slope, elevation, population density, soil and land use/land cover (LULC). The study area was categorized into four suitability zones: high, moderate, low, and very low, representing 43.22%, 16.09%, 28.16%, and 12.53% of the area, respectively. The locations were selected based on the optimal distances considered for efficient waste management. The final results were validated using a receiver operating characteristic (ROC) curve, which utilized a randomly selected set of 50 potential landfill site locations. The analysis demonstrated good accuracy, with the area under the curve (AUC) indicating that 84% of the results effectively validated the spatial analysis. To achieve sustainable solid waste management, planners should consider implementing alternative strategies such as source reduction, composting, sanitary landfills, and public awareness programs. The resulting map provides potential sites for landfilling waste, which can aid urban planners and authorities in implementing effective urban waste management strategies.

Returns Management of Maize and Paddy Seeds

This study focuses on examining the returns management processes in the selected seed firm, particularly for maize and paddy seeds in the Telangana districts of Karimnagar and Nizamabad. The research identifies significant challenges in managing seed returns, such as inefficiencies that affect seed quality and availability, as well as the financial costs involved in handling returns. The study underscores the importance of a well-organized returns management system, especially since approximately 15 per cent of seed returns occur every year. Viable seeds are reprocessed and stored for future use, while non-viable seeds are safely disposed of or repurposed for other uses. The financial transactions associated with the returns process are carefully managed, ensuring efficient compensation for distribution partners. The findings highlight that an effective returns management process is crucial for preserving seed quality, minimizing waste and improving customer satisfaction. The study concludes with suggestions for refining the returns management process to bolster the sustainability and competitiveness of the selected firm. This manuscript offers valuable insights for researchers, policymakers and industry professionals involved in the agricultural supply chain.

Prompt engineering techniques for semantic enhancement in business process models

PurposeThe term knowledge refers to the part of the world investigated by a specific discipline and that includes a specific taxonomy, vocabulary, concepts, theories, research methods and standards of justification. Our approach uses domain knowledge to improve the quality of business process models (BPMs) by exploiting the domain knowledge provided by large language models (LLMs). Among these models, ChatGPT stands out as a notable example of an LLM capable of providing in-depth domain knowledge. The lack of coverage presents a limitation in each approach, as it hinders the ability to fully capture and represent the domain’s knowledge. To solve such limitations, we aim to exploit GPT-3.5 knowledge. Our approach does not ask GPT-3.5 to create a visual representation; instead, it needs to suggest missing concepts, thus helping the modeler improve his/her model. The GPT-3.5 may need to refine its suggestions based on feedback from the modeler.Design/methodology/approachWe initiate our semantic quality enhancement process of a BPM by first extracting crucial elements including pools, lanes, activities and artifacts, along with their corresponding relationships such as lanes being associated with pools, activities belonging to each lane and artifacts associated with each activity. These data are systematically gathered and structured into ArrayLists, a form of organized collection that allows for efficient data manipulation and retrieval. Once we have this structured data, our methodology involves creating a series of prompts based on each data element. We adopt three approaches to prompting: zero-shot, few-shot and chain of thoughts (CoT) prompts. Each type of prompting is specifically designed to interact with the OpenAI language model in a unique way, aiming to elicit a diverse array of suggestions. As we apply these prompting techniques, the OpenAI model processes each prompt and returns a list of suggestions tailored to that specific element of the BPM. Our approach operates independently of any specific notation and offers semi-automation, allowing modelers to select from a range of suggested options.FindingsThis study demonstrates the significant potential of prompt engineering techniques in enhancing the semantic quality of BPMs when integrated with LLMs like ChatGPT. Our analysis of model activity richness and model artifact richness across different prompt techniques and input configurations reveals that carefully tailored prompts can lead to more complete BPMs. This research is a step forward for further exploration into the optimization of LLMs in BPM development.Research limitations/implicationsThe limitation is the domain ontology that we are relying on to evaluate the semantic completeness of the new BPM. In our future work, the modeler will have the option to ask for synonyms, hyponyms, hypernyms or keywords. This feature will facilitate the replacement of existing concepts to improve not only the completeness of the BPM but also the clarity and specificity of concepts in BPMs.Practical implicationsTo demonstrate our methodology, we take the “Hospitalization” process as an illustrative example. In the scope of our research, we have presented a select set of instructions pertinent to the “chain of thought” and “few-shot prompting.” Due to constraints in presentation and the extensive nature of the instructions, we have not included every detail within the body of this paper. However, they can be found in the previous GitHub link. Two appendices are given at the end. Appendix 1 describes the different prompt instructions. Appendix 2 presents the application of the instructions in our example.Originality/valueIn our research, we rely on the domain application knowledge provided by ChatGPT-3 to enhance the semantic quality of BPMs. Typically, the semantic quality of BPMs may suffer due to the modeler's lack of domain knowledge. To address this issue, our approach employs three prompt engineering methods designed to extract accurate domain knowledge. By utilizing these methods, we can identify and propose missing concepts, such as activities and artifacts. This not only ensures a more comprehensive representation of the business process but also contributes to the overall improvement of the model's semantic quality, leading to more effective and accurate business process management.

Quality management in public administration. Legal and administrative regulations and effective process management

A quality-based public organisation creates its own quality culture, which determines the value-giving activities and processes and the behaviour and attitudes of their participants. This culture is created by the commitment of top management through its contribution to promoting a quality approach. An organisation that adheres to the principles of quality management standards is committed to identifying the processes within the quality management system, together with their sequence and interdependencies (process approach). By locating the necessary resources in the processes, it is possible to manage them in such a way as to deliver value and achieve results for the relevant stakeholders (customer orientation, relationship management). At the same time, the systems approach provides an opportunity for top management (leadership) to optimise them in the short and long term as a consequence of decisions taken. The aim is to continuously implement the measures necessary to achieve the set results and continuous improvement (enhancement). The quality management system provides the opportunity to apply the organisation's natural approach to effective and efficient management by defining monitoring methods and ways of evaluating them (fact-based decision-making). Also, in order to manage effectively and efficiently, it is non-negligible to involve employees at all levels. As participants in the processes defined in the sys-tem, they contribute directly to the results achieved (people involvement).

Optimization of algorithms for effective management of the measurement process in electrical impedance tomography and ultrasonic tomography

The article discusses the design of advanced embedded algorithms that aim to manage and control the measurement process using the Electrical Impedance Tomography and Ultrasonic Tomography methods. The project aims to develop solutions that optimize the performance of embedded devices that must operate on limited resources such as memory, computing power, or bandwidth. Minimizing energy consumption is an important aspect, especially for battery-powered devices. Algorithms must also be adapted to specific hardware constraints, such as low RAM or CPU limitations, which require complex engineering and optimization. Additionally, the project assumes the implementation of algorithms that consider security aspects, which is crucial in protecting data processed and transmitted by the device. It also requires the development of effective communication methods between the embedded device and other systems, including appropriate communication protocols.

Machine Learning Analysis Using the Black Oil Model and Parallel Algorithms in Oil Recovery Forecasting

The accurate forecasting of oil recovery factors is crucial for the effective management and optimization of oil production processes. This study explores the application of machine learning methods, specifically focusing on parallel algorithms, to enhance traditional reservoir simulation frameworks using black oil models. This research involves four main steps: collecting a synthetic dataset, preprocessing it, modeling and predicting the oil recovery factors with various machine learning techniques, and evaluating the model’s performance. The analysis was carried out on a synthetic dataset containing parameters such as porosity, pressure, and the viscosity of oil and gas. By utilizing parallel computing, particularly GPUs, this study demonstrates significant improvements in processing efficiency and prediction accuracy. While maintaining the value of the R2 metric in the range of 0.97, using data parallelism sped up the learning process by, at best, 10.54 times. Neural network training was accelerated almost 8 times when running on a GPU. These findings underscore the potential of parallel machine learning algorithms to revolutionize the decision-making processes in reservoir management, offering faster and more precise predictive tools. This work not only contributes to computational sciences and reservoir engineering but also opens new avenues for the integration of advanced machine learning and parallel computing methods in optimizing oil recovery.

Water Tales from Turkistan: Challenges and Opportunities for the Badam-Sayram Water System under a Changing Climate

The Badam River, a tributary to the Arys River located in the Syr Darya basin, is a crucial natural resource for ecological, social, and economic activities in the semi-arid region of southern Kazakhstan. The river basin is heavily influenced by manmade water infrastructure and faces water scarcity, particularly during summer, highlighting the importance of understanding its hydrological processes for effective water resource management. In this study, a semi-distributed conceptual hydrological model of the Badam River was implemented using the RS MINERVE hydrological software to evaluate the impacts of climate change on hydrology and to test the resilience of the water system. Connected HBV models were implemented for each of the hydrological response units that were defined as altitudinal zones. The hydrological model was calibrated using daily time steps between 1979 and 2011, and the resulting flow exceedance curves and hydrographs were used to assess the potential impacts of climate change on the basin, using CMIP6 precipitation and temperature scenarios. Future climate scenarios for the 2054 – 2064 period demonstrate that the peak discharge will be shifted to spring/late spring compared to the current early summer with no significant decrease in average discharge per day of the year. The insights gained from this hydrological-hydraulic model can be used to effectively manage the water system and inform future hydropower design decisions and serve as a blueprint for similar studies in the region and elsewhere.

Unpacking the relationship between cultural diversity and workgroup creativity

PurposeThis study aimed to illustrate the conditions under which cultural diversity enhances workgroup creativity. It does so by investigating the impact of ethnic diversity on workgroup creativity through the mediating mechanisms of cognitive diversity and information elaboration, while also exploring the role of inclusive leadership in this process.Design/methodology/approachMulti-source data was collected from a sample of 338 employees nested within 56 workgroups across three distinct organizations. Conditional process analysis was used to empirically test the proposed hypotheses.FindingsThe results show that ethnic diversity, a surface-level cultural attribute, contributed to diversity in deep-level cognitive resources, and that workgroups were able to capitalize on these variations in deep-level cognitive resources to enhance their creativity when they engaged in the elaboration of task-relevant information. Results also demonstrated that the effective management of workgroup processes through inclusive leadership helped materialize the performance-promoting effects of cultural diversity. Overall, the findings support the notion that cultural diversity is indeed beneficial to workgroups.Originality/valuePrior research has typically examined cultural diversity in workgroups from the perspective of either surface-level or deep-level cultural attributes, leading to conflicting findings. Our study takes a multifaceted approach to cultural diversity and its influence on workgroup creativity, offering a more nuanced understanding. Additionally, by integrating the concept of inclusive leadership, a relatively new conceptualization of leadership specifically relevant to diverse workgroups, we clarified strategies for fostering positive workgroup performance.

Change management through strategic leadership: the mediating effect of knowledge management in public organizations, Ethiopia

The purpose of this study is to investigate the effects of strategic leadership on change management within public organizations, mediated by knowledge management. In this study, an explanatory design and a quantitative approach were employed. A structured questionnaire survey was administered to 366 randomly selected respondents from public organizations in northwest Ethiopia. The reliability and validity of the scale items were rigorously assessed, and the data were analyzed using partial least squares structural equation modeling. The findings reveal the direct effects of strategic leadership and knowledge management on change management, with knowledge management partially mediating the relationship between strategic leadership and change management. The study addresses a significant gap in the literature by shedding light on how strategic leadership drives change in public organizations. Its interdisciplinary approach and examination of mediation offer original insights, paving the way for future studies on challenges within public service contexts. Recommendations underscore the importance of considering local context, embracing adaptive leadership, and integrating knowledge processes for effective change management in public organizations.

Design and management considerations for the Kenya-Tanzania marine transboundary conservation area.

Although transboundary conservation areas (TCAs) are critical tools for protecting ecosystems and ecological processes that transcend national jurisdictions, they are challenging to create due to the differences in governance contexts and capacity and power dynamics among countries. Marine TCAs are also more difficult to enforce relative to terrestrial TCAs because most nations still treat oceans as open access. Current guidelines for TCA development and implementation also focus mostly on terrestrial TCAs, which are not practical for marine TCAs. Hence, we reviewed the challenges associated with the design and management of marine TCAs and devised analytical and practical approaches to support the application of spatial planning frameworks and adaptive governance mechanisms. We used the lessons from the review to examine the decisions made for the proposed marine TCA in the Kenya-Tanzania border region and created options and considerations to promote effective design and management processes. We found the obstacles to marine TCAs in general are related to issues of fit, particularly differences in environmental research capacity, socioeconomic contexts, and internal institutional arrangements. These included differences in knowledge and capacity for marine ecological research and conservation; ability to adjust and update data; differences in values, interests, and resource uses; conservation costs; jurisdictional differences; engagement of multiple levels of organization; and differences in legal bases and policy development processes. Understanding and reconciling these challenges during the TCA development process can help enhance meaningful discussions in the design of the TCA and cultivate the enabling conditions for collaborative governance across countries and within different levels of organization from national to local actors.