Product Portfolio Research Articles

State and trends in the development of the microfinance market in Russia

The relevance of the article is due to the insignificant contribution of microfinance to the development of the Russian economic system, especially in the context of supporting small and medium-sized businesses. However, the regulator sees it as a promising sector of the financial market and considers its progressive development necessary. The purpose of the work is to study the current state and identify trends in the development of the microfinance market in Russia. The methodological basis of the study includes empirical observation and analysis. During the work, official statistical data and scientific publications on the topic of microfinance have been used. The article provides a review of current legislative documents regulating the microfinance sector, and analyses the state of the market based on statistical data. It is substantiated that some elements of the monetary and financial policies pursued in the Russian Federation can be applied for the successful development of the microfinance sector, contribute to its effective and balanced work, and improve accessibility and sustainability. In the course of the work, key directions for the development of the microfinance market are formed: improving regulation and supervision; promoting financial literacy of the population; application of digital technologies; expansion and diversification of the product portfolio, development of partnerships, social entrepreneurship, which contribute to the sustainable development of this segment of the financial market. Particular attention is paid to a detailed analysis of improving the regulatory framework for microfinance in Russia from the point of view of legislation on bankruptcy of individuals, stimulating innovation and digitalisation, and supporting social entrepreneurship.

Competitive Strategies and Performance of Beverages Companies in Rwanda: A Case Study of Bralirwa Plc

Purpose: The purpose of this study was to assess the effects of competitive strategies on the performance of Beverages companies in Rwanda, specifically in Bralirwa Plc. The study specifically sought to determine the effect of cost leadership strategy, differentiation strategy, focus strategy, and differentiation Focus Strategy on the performance of Bralirwa Plc. Methodology: This research was descriptive research design, and the study population comprise 206 employees of Bralirwa Plc/Kigali office. Using simple random sampling technique, a sample size of 136 respondents was established using Slovin formula. The researcher used primary data in this study. A closed end questionnaire was utilized. Financial statements of Bralirwa Plc during 10 years period (2014-2023) were also analyzed. Correlation analysis was utilized to assess the data and results generalized for the entire population, while multiple regression was used to test hypotheses. To compute and analyze the data in this study, available statistical product for service solution (SPSS 27) was used. Findings: The correlation analysis revealed a strong positive and significant relationship between cost leadership strategy and performance (r=0.989 and sig=.000<0.01), between differentiation strategy and performance (r=0.944 and sig=.000<0.01), between focus strategy and performance (r=0.961 and sig=.000<0.01) and between differentiation focus strategy and performance (r= 0.945 and sig=.000<0.01) level of significance. The regression analysis revealed that cost leadership contribute 97.9% on the performance in Bralirwa Plc that differentiation strategy contributes 89.2% of the performance in Bralirwa Plc, that focus strategy contributes 92.4% of the performance in Bralirwa Plc, and that differentiation focus strategy contributes 89.3% of the performance in Bralirwa Plc. The study concluded that there were significant and positive effects between Competitive strategies and performance of Bralirwa Plc. Unique Contribution to Theory, Practice and Policy: The study recommended Bralirwa to invest in market research, diversifying product portfolios, and implementing targeted marketing strategies to identify emerging trends and consumer preferences, thereby reinforcing Bralirwa's commitment to differentiation and market leadership.

From Local Markets to Global Success: A Case Study on Scaling and Innovating in the Food Manufacturing Company

This paper aims to analyze the development process of a famous food manufacturing company that started only in local farmer markets aiming at snacks and agricultural products. Looking back at the different fiscal years, the company has acquired numerous accomplishments, hence attributing it to a strong focus on quality and innovation. There are several serious issues that a company faces while the strategies revealed above are to establish and consolidate a position in the rapidly growing food manufacturing industry. Some of these are the challenges of globalization, diversification of product portfolio, sustaining innovation, and building a strong and easily identifiable brand. In this paper analyzing the specifics of the company’s development, its strategic directions, and defining the major issues and problem-solving approaches in responding to these complex challenges a certain group of questions will be highlighted. The paper discusses the factors that have facilitated the effectiveness of its strategic management concerning the achievement of the firm’s goals and sustained growth amidst challenges. From the examination of the company’s strategic choices, operating changes, and patterns of analyzing the market environment, this study has gone a long way in establishing the key dynamics underlying operation scaling within the food manufacturing industry. The lessons from this case suggest that to sustain a commitment and build a highly competitive mass-market business over time there is a need for flexibility, creativity, and vision.

Microsoft's Strategic Advantage: An In-depth Analysis Based on Porter's Five Forces Model

Abstract: This article uses Michael Porter's five forces model to analyze Microsoft's competitive situation in the global technology industry. It emphasizes that Microsoft has maintained its industry leadership by continuously innovating its technology and being keenly aware of market changes. The analysis covers Microsoft's strategies in facing market competition, the threat of new entrants, the challenge of substitute products, the bargaining power of suppliers and buyers, and its impact on the company's performance. The study pointed out that Microsoft has established high barriers to entry in its main business areas, thereby effectively preventing the entry of new competitors. The article also analyzes how Microsoft maintains its competitive advantage and market leadership through product differentiation, innovation, flexible pricing strategies, and the ability to adapt to market structure. Although Microsoft faces many challenges, it has successfully maintained its competitiveness in the global market through solid R&D capabilities, an extensive product portfolio, deep market penetration, and an active response to changes globally.

Standing out while fitting in: An objective measure of visual branding cohesion across a product portfolio

This research develops a new metric (PBCM) that can identify products within a portfolio that are eroding visual branding cohesion. We show how this new measure gives results equivalent to consumer evaluations of cohesion, without costly and time intensive data collection. The sampling frame for this research is 10 portfolios from five categories (dry dog food, instant coffee, toothpaste, shower gel and chewing gum) in the United Kingdom. In addition, 626 consumers were surveyed to investigate how PBCM affects a consumer’s ability to match an individual product back to its portfolio and recall the brand name. We find that products from high cohesion portfolios have significantly higher (17%) correct brand recall than those from low cohesion portfolios and are matched back to their portfolio by more than twice as many respondents (79% v 35%), significantly faster (2.3 vs. 3.8 minutes).

Analysis of implementation factors of management systems – case of the Republic of Croatia

Management systems can serve as a foundation for more efficient and effective organizational management. By certifying their management system, an organization demonstrates its commitment to excellence and focus on meeting interested parties’ requirements. However, certification is determined by the decision of the organization’s management, which can be influenced by various factors such as the organization’s size, the market in which it operates, market opportunities, availability of financial resources, the organization’s product portfolio, and more. Therefore, the aim of this research is to identify the factors that influence the management’s decision to initiate the certification process and certify the management system. The research was conducted on a sample of 320 business entities registered in the Republic of Croatia. The research instrument was a questionnaire, and the research results can be used to compare different countries in the Western Balkans region or European Union member states.

Data-driven inventory control for large product portfolios: A practical application of prescriptive analytics

Motivated by the real-world inventory management problem of a large network of pharmacies, this paper proposes and studies a practically relevant Prescriptive Analytics approach for data-driven dynamic inventory control of large portfolios of interrelated products. We extend existing research on weighted Sample Average Approximation by integrating a ‘global learning’ model that effectively exploits cross-learning opportunities within the product portfolio. The results of an extensive numerical evaluation on real-world data suggest that our approach outperforms relevant benchmarks—in particular, models that rely on ‘local learning’ strategies where weight functions are trained separately for each product. The numerical results also allow us to derive important practical and structural insights regarding the value of contextual information in our global learning framework.

Smart design and additive manufacturing of bending tools to improve production flexibility

For the automotive industry, especially on the part of Tier 1 and Tier 2 suppliers, the future will be about maintaining sovereignty in the form of technology openness and accelerating digitization. The product portfolio, which is generally passed on by OEMs to suppliers for production, often includes body parts that cannot always be manufactured economically with the prevailing production technology. The reason for this is a high diversity of model-variants, which requires smaller batches. To this end, highly flexible large-series production cells for body sheet components that can be scaled in all dimensions are being developed and tested. For the first time, they will make it possible to redesign the process planning in series production on a component-specific basis. The aim is to reduce production costs for new, geometrically different component variants. The basic components of the flexible manufacturing system are, firstly, new flexible forming technologies which have the potential to produce typical vehicle part geometries. Secondly, a process generator develops the corresponding production plan. A digital mapping of the manufacturing processes enables the selection of cost-, efficiency-, flexibility- and resilience-optimized production chains depending on the number of parts. Established manufacturing processes to produce car body components are supplemented in the cell by flexible processes such as 3D swivel bending. As a use case for flexible manufacturing, a concept for Rapid Tooling of 3D swivel bending tools is developed. In the flexible manufacturing system to be developed, a method of a standardized process sequence to produce forming tools within 24 h has been lacking to date. For this purpose, the concept of an automated design is being developed in which a reconfigurable tool body can be sliced into sheet metal stripes The active tool surface is additively manufactured after the tool has been packaged using LMD and adapted to individual requirements. The goal in the application of Rapid Tooling is to reduce lead times and development costs through a largely automated tool design and lead time-optimized manufacturing concept.

A comprehensive physicochemical characterization and proposed portfolios of applications for the fruits and seeds of 11 accessions of Jatropha curcas L.

The seed oil and extraction cake from 11 accessions of Jatropha curcas from Mexico, El Salvador, and India were comprehensively characterized with the objective of selecting parentals based on desirable traits for a hybridization program. Kernels contained up to 65 % oil and up to 30 % protein. The most abundant protein types were glutelins (48 %) and globulins (24 %), with arginine (0.096 mg/g) and leucine (0.070 mg/g) being the major amino acids. Glucose (0.09 g/g) and arabinose (0.03 g/g) were the most abundant carbohydrates. The oil was primarily composed of oleic (41 %) and linoleic (37 %) acids. The physicochemical properties of the oil included an acid value of 0.28–1.15 %, saponification value of 155–208 mg KOH/g, iodine value of 0.97–1.08 g I2/g, and viscosity of 21.9–40.9 cSt at 40 °C. Six accessions were selected as parental candidates based on their potential as feedstock for a diverse portfolio of products. The most common applicability of oils were lubricants, biopolymers, biofertilizer, and liquid biofuels production. One Mexican accession had a phorbol-ester concentration much lower than the toxicity threshold (0.06 mg/g) and a high protein content, making it attractive for the animal feed industry and for protein extraction. The selected accessions are preserved in a local germplasm bank and will be used for continued genetic improvement through hybridization, aiming to preserve the identified traits while increasing fruit productivity.

Product portfolio decarbonization: Deleting hot products for a cooler supply chain

AbstractModern economic development emphasizes the reduction of carbon emissions. In rationalizing product portfolios, organizations must prioritize low‐carbon development by selecting products with minimal emissions. Eliminating high‐emission items can create opportunities for new low‐carbon products, thereby enhancing competitiveness. In this study, we propose a hybrid mixed method that integrates text mining and multi‐objective optimization algorithms, utilizing a broad range of quantitative and qualitative data sources, including online consumer reviews. We apply this method to a real case in the Chinese air‐conditioning industry for practical validation. The results indicate that for comprehensive product portfolio decarbonization, organizations should consider deleting high‐performing products (e.g., those with strong sales and market performance) to achieve full decarbonization across the entire supply chain. This approach offers valuable insights for managers aiming to simultaneously improve economic and environmental performance.

Economic validation and comparison of microbial tryptophan, erythritol and collagen production in an integrated sugarcane biorefinery

Low sugar prices present a significant challenge to the global sugarcane industry, prompting the exploration of diversification strategies for expanding product portfolios. Techno-economic analyses and environmental sustainability assessments were carried out to evaluate the microbial production of tryptophan, erythritol, and collagen from A-molasses in a biorefinery annexed to an existing sugarcane mill. Tryptophan production exhibited the highest profitability, with a minimum selling price (MSP) at 59.7 % of its current market price, although the achievable production volumes of tryptophan from one sugar mill would oversupply the global market. Due to the larger market size of for collagen the achievable production capacity in the collagen scenario would avoid market saturation, reducing the risk of oversupply and rendering it more economically viable. In contrast, erythritol production was marginally not profitable, with an MSP exceeding the current market price by 1 %, primarily attributed to high operational costs. All scenarios demonstrated relatively low greenhouse gas (GHG) emissions (ranging from 9.1 to 16.5 kg CO2eq/kg product), with tryptophan production emerging as the most environmentally favourable option due to minimal chemical and freshwater usage. When compared with literature-reported data on ethanol and short-chain fructooligosaccharides (scFOS), only collagen and ethanol production were deemed viable, based on their favourable profitability and contribution to the market.

Simulation of Discovering Market Opportunities Using AI Methods

Due to the strong turbulence that exists in the business environment, the view is sometimes articulated that the time horizon of decisions is no longer a hallmark of strategic management. Opposing views argue that a turbulent environment changes the trajectory of reaching future objectives determined by strategic decisions. Such trajectories require the company to be agile, which is manifested by seizing opportunities. Opportunities arise because the environment is volatile. An example of market opportunity is the unsatisfied demand for products. Buyers are driven by different motives when choosing between products that are alternative to them. From the producer's point of view, the purchase is therefore random. As a consequence, the alignment of the offered product portfolio with the actual purchasing decisions of customers is undetermined. In this article, we address the problem of determining the product portfolio structure expected by customers, i.e. one that is consistent with their future purchasing decisions. We hypothesise that this problem can be represented by a model of flows between alternative resources. Problems of this type are solved using Markov Chain Monte Carlo (MCMC) methods. In order to discover the expected demand (opportunity), we simulated the flow model we developed using the Metropolis-Hastings algorithm, which is a special case of the MCMC method used in AI. Due to operating on numerical data, such simulations fall under quantitative research. In the article, we present a model of customer flows between alternative products and then the simulation result, which is the expected value of these flows (stationary point). We convert this value into the structure of the product portfolio using a model of customer purchasing decisions that we have developed. The obtained results confirm the effectiveness of our method and have significant practical value, especially for SMEs. It also enables the assessment of the company's product strategy based on real sales data. The application of our methodology is limited to discovering opportunities in situations where purchasing decisions are influenced by variable environmental factors, causing irregular purchases by individual customers. It is useful, for example, in discovering opportunities in markets such as Household Articles, Furniture, Vehicles, Equipment Repairs, Construction, and many others.

Sentiment Mining in E-Commerce

Sentiment analysis is crucial for comprehending customer feedback and enhancing workplace culture, as well as improving products and services. By employing natural language processing (NLP) techniques to meticulously analyze this feedback, organizations can identify specific areas that require improvement, address employee issues, and cultivate a positive work environment. These deep learning models powered by NLP offer invaluable tools for HR and sales departments in the e-commerce sector, enabling them to track sentiment trends among employees and users over time and implement targeted interventions. Focusing on the e-commerce industry, this study employs NLP-driven deep learning methodologies to analyze both employee and user feedback, with the objective of identifying underlying sentiments. The proposed framework leverages these advanced techniques to categorize user feedback into positive, negative, or neutral sentiments. This approach aims to develop a robust and effective system for sentiment analysis, providing significant insights that can help drive organizational improvements and enhance customer satisfaction. The key steps of this framework include data collection, NLP-enhanced feature extraction, sentiment detection, and final classification using finite-state automata. The effectiveness of this NLP-centric approach was tested on diverse datasets of customer feedback collected from an e-commerce industry. Evaluation metrics such as accuracy, precision, and recall were utilized to assess the performance of the system. The results demonstrate the effectiveness of the proposed framework, achieving a 93.75% accuracy rate and surpassing existing benchmark methods. The outcomes of this study are particularly consequential for the e-commerce sector, offering them a strategic advantage in refining their product portfolios and cultivating a more dynamic workplace culture

Unconventional Edible Plants of the Amazon: Bioactive Compounds, Health Benefits, Challenges, and Future Trends.

The pursuit of an improved quality of life is a major trend in the food market. This is driving the reformulation of the industry's product portfolio, with the aim of providing nourishment while also contributing to beneficial health metabolic processes. In this context, the use of local biodiversity and the recovery of the traditional knowledge associated with the consumption of vegetables that grow spontaneously in nature emerge as more sustainable and nutritionally adequate concepts. The Amazon region is known for its abundant biodiversity, housing numerous unconventional food plants whose nutritional and biological properties remain unknown due to a lack of research. Among the different species are Xanthosoma sagittifolium, Acmella oleracea, Talinum triangulare, Pereskia bleo, Bidens bipinnata, and Costus spiralis. These species contain bioactive compounds such as apigenin, syringic acid, spilanthol, and lutein, which provide various health benefits. There are few reports on the biological effects, nutritional composition, bioactive compounds, and market prospects for these species. Therefore, this review provides an overview of their nutritional contribution, bioactive compounds, health benefits, and current market, as well as the use of new technologies that can contribute to the development of functional products/ingredients derived from them.

Assessing Product Use Behavior and Exposure: Definitions and Methods

Summary In recent years, the tobacco- and/or nicotine-containing product (TNP) portfolio has expanded to include products such as e-vapor products, heated tobacco products, and nicotine pouches. Although scientific papers and regulatory requirements/recommendations related to the assessment of product use behavior and exposure to product use have been published for these novel TNPs, there is great diversity in the terminology used to characterize and assess these types of products. The aim of this paper is to define the terms and methods used for assessing product use behavior and exposure, with the objective to suggest a uniform application of terms used by scientists working in this field of research. This publication is the work product of a cross-industry work item commissioned by the Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) Product Use Behaviour and Biomarkers Subgroups.

HydroSAR: A Cloud-Based Service for the Monitoring of Inundation Events in the Hindu Kush Himalaya

The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service which was co-developed with in-region partners to provide year-round, low-latency weather hazard information across the HKH. This paper describes the end user-focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR’s broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring the surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which provides the capability to scale automatically with the event size. A performance assessment of our quantitative algorithms is described, demonstrating the capabilities to map the flood extent and water depth with an accuracy of >90% and <1 m, respectively. An application of the HydroSAR service to the 2023 South Asia monsoon seasons showed that monsoon floods peaked near 6 August 2023 and covered 11.6% of Bangladesh in water. At the peak of the flood season, nearly 13.5% of Bangladesh’s agriculture areas were affected.

Optimising picking operations in distribution centres: a simulation and algorithm-based approach for travel distance reduction

Abstract This study examines the pivotal role of the logistics sector in corporations, particularly those with diverse product portfolios. It focuses on the time-intensive “picking” process, driven by various products and material handling requirements for order fulfilment. The research presents a methodology that combines distribution centre modelling for simulation with an optimisation algorithm to enhance operational efficiency. The goal is to determine an optimal route for product retrieval, minimising employee travel distances, using the simulated annealing algorithm. The results showcase a significant 7 % reduction in employee travel distance during collection. This research is relevant to academia and practical applications as it presents an opportunity to reduce operational costs in distribution centres, enhance the efficiency of picking operations, and improve the competitiveness of companies. Furthermore, it contributes to operations research by addressing a complex problem with significant practical implications using a rather unused method to solve this problem of picking operations. The approach is empirically applied in a prominent Brazilian beverage company. This methodology proves valuable for optimising logistics operations in various industrial contexts, highlighting its practical applicability.

Life cycle-based multi-objective model for optimal gaseous fuel generation and portfolio allocation in gas grids: A strategic decarbonization

Biomethane and hydrogen are acknowledged as transformative opportunities for decarbonizing the conventional gas grid. Essential to this transformation is the modeling of the gaseous fuel supply chain, particularly with hydrogen and biomethane, offering crucial insights for decision-makers. This study introduces a life cycle thinking-based multi-objective optimization model for the integrated design of biomethane and hydrogen gaseous fuel supply chain networks. The model determines optimal resource allocation for the production of the two fuels, integrating them into the conventional gas network. Moreover, it allocates conventional natural gas, biomethane, and hydrogen optimally across building, industry, and transport sectors, considering the life cycle environmental and economic performance of fuel integration paths. Objective functions include minimization of life cycle emissions and levelized cost of energy while maximizing revenue from fuel sales. Integrating life cycle assessment and cost analysis tools, the optimization model quantifies emissions and life cycle costs for biomethane and hydrogen paths. Results identify Pareto-optimal fuel production paths and portfolios, revealing that integrating the alternative fuels into the current gas grid can significantly reduce emissions (up to 250 tonCO2eq/year) and generate substantial carbon tax savings (up to $16,250/year). This model is useful for gaseous fuel industry stakeholders, offering a comprehensive view of supply chain costs and detailed insights into emission benefits when integrating alternative fuels into existing gas networks.

Analysis of MA in the Vehicle Industry: Evidence from Geely’s Acquisition of Lotus

As a matter of fact, mergers and acquisitions (M&A) in the global vehicle industry have become increasingly common especially in recent years, driven by various factors such as technological advancements, market expansion, and brand strengthening. In reality, this trend is exemplified by Geely’s acquisition of the British sports car brand, Lotus. With this in mind, this study aims to analyze the motivation, process as well as impact of this acquisition, employing methods like SWOT analysis and market research. According to the analysis, the findings reveal that the acquisition not only enhances Geely’s global market presence but also complements its product portfolio with Lotus’s unique technology and brand heritage. Furthermore, the integration of Lotus into Geely’s operations offers opportunities for synergies and cost savings. At the same time, the implications of the study are proposed. This research contributes to the understanding of M&A strategies in the automotive sector, providing insights for both academic and industry practitioners.

Analyzing the reasons for Apple’s success

Apple is a technological company that designs and manufactures personal computers, smartphones, tablets, and related accessories. The portfolio of Apple products includes the iPhone, MacBook, iPad, Apple Watch, and Apple TV. It also gets consumers various software applications such as iOS, macOS, watch OS, Apple Pay, Apple Care, and iCloud. Digital content is sold through the App Store, Apple Music, and News. The company’s business spreads universally in the Americas, Europe, the Middle East, Asia, and Africa, with headquarters in Cupertino, California. It is the most valuable publicity traded company worldwide, with US$394.3 billion in 2022 revenue.