Production Management Research Articles

Comparative Analysis of K-Means and K-Medoids Algorithms for Product Sales Clustering and Customer

In today's rapidly evolving business landscape, effective product management is crucial for maintaining a company's competitive advantage. Comprehensive analysis is essential for providing insights that inform strategic business development decisions. This study examines the sales data of PT XYZ from July 2020 to May 2024 using the K-Medoids algorithm, with dimensionality reduction applied through Principal Component Analysis (PCA). The clustering results identified three customer segments: Cluster 1 with 46 customers, Cluster 2 with 76 customers, and Cluster 3 with 62 customers. For product segmentation, four clusters were identified: Cluster 1 with 52 products, Cluster 2 with 12 products, Cluster 3 with 20 products, and Cluster 4 with 53 products. The K-Medoids algorithm demonstrated superior performance compared to K-Means in terms of cluster separation and interpretability, with visualizations that enhance the understanding of customer and product distributions. This research aids the company in enhancing customer satisfaction, optimizing inventory, and increasing profitability.

Construction of a blockchain based cold chain logistics information platform for Gannan navel oranges to enhance transparency and efficiency

As a high-value agricultural product, the cold chain logistics management of Gannan navel oranges has global significance. Especially in Africa and Europe, food safety and supply chain quality are critical issues. However, the existing Gannan navel orange logistics information management system relies on traditional databases and information systems, with insufficient data sharing and transparency, affecting the overall coordination of the supply chain and customer satisfaction. In addition, the traditional system is vulnerable to hacker attacks and malicious tampering of data by insiders, resulting in serious economic losses and reputation damage. So the blockchain platform constructed in this study improves the transparency and traceability of logistics data through the SMART-PBFT algorithm of the alliance chain, which optimizes the logistics management process, improves the quality of logistics services, and reduces operating costs. It improves the logistics efficiency and data transparency of local agricultural products, and also provides a demonstrative case for the cold chain management of other high-value agricultural products around the world, with broad application potential and reference value.

The Impact of Blockchain Technology on E-commerce Product Development: Case Studies of Walmart and LVMH

In the current digital era, the emergence of blockchain technology has profoundly impacted business models, especially in e-commerce. Blockchain technology brings new opportunities and challenges to product sales, transactions, and management. This study examines the impact of blockchain technology on the development of e-commerce products, particularly through the cases of Walmart and Louis Vuitton (LVMH). It demonstrates the application of blockchain and its effects on product traceability, anti-counterfeiting verification, data transparency and privacy protection. It was found that blockchain technology improves data security and user trust, reduces transaction costs, and enhances supply chain management efficiency. However, blockchain also needs help regarding energy consumption, performance bottlenecks, privacy protection, inconsistent technical standards, and unclear laws and regulations. It is necessary to take appropriate measures to reduce risks and ensure the effective application of technology. This study concludes with a series of recommendations to promote the effective application of blockchain technology in e-commerce to facilitate the e-commerce industry's sustainable development.

Social and Economic Problems of Agricultural Enterprises: The Case of Bayburt

Agricultural enterprises are enterprises that make significant contributions to the economic, social and cultural development of countries by engaging in agricultural production, agricultural product processing and agricultural marketing activities. It can be said that agricultural enterprises in Türkiye face many problems because they are mostly SMEs. The aim of this study is to examine the social and economic problems of agricultural enterprises based on the Bayburt example. In the study, it was deemed appropriate to use face-to-face interview technique within the scope of qualitative research method. In the interview, a questionnaire containing 32 questions about the social and economic problems of agricultural enterprises was used in addition to questions about participants and agricultural enterprises such as position, sector experience, enterprise size, enterprise title. Data were collected from 27 agricultural enterprises engaged in production, processing and marketing activities in Bayburt province. Content analysis technique was used to analyze the data. The responses of the participants were processed in depth within the scope of the themes determined in accordance with the content analysis technique, and the social and economic problems of agricultural enterprises were identified and solution suggestions were developed. As a result of the analysis, it was determined that agricultural enterprises have various problems related to management, production, marketing, finance and risk management, accounting, human resources, R&D and infrastructure, and suggestions were made within the scope of each theme. In conclusion, it is thought that this study will shed light on all agricultural enterprises operating in the sector and relevant stakeholders by addressing the existing problems, identifying the obstacles and developing recommendations.

Comprehensive Review of Biomass Pyrolysis: Conventional and Advanced Technologies, Reactor Designs, Product Compositions and Yields, and Techno-Economic Analysis

Pyrolysis is an environmentally friendly and efficient method for converting biomass into a wide range of products, including fuels, chemicals, fertilizers, catalysts, and sorption materials. This review confirms that scientific research on biomass pyrolysis has remained strong over the past 10 years. The authors examine the operating conditions of different types of pyrolysis, including slow, intermediate, fast, and flash, highlighting the distinct heating rates for each. Furthermore, biomass pyrolysis reactors are categorized into four groups, pneumatic bed reactors, gravity reactors, stationary bed reactors, and mechanical reactors, with a discussion on each type. The review then focuses on recent advancements in pyrolysis technologies that have improved efficiency, yield, and product quality, which, in turn, support sustainable energy production and effective waste management. The composition and yields of products from the different types of pyrolysis have been also reviewed. Finally, a techno-economic analysis has been conducted for both the pyrolysis of biomass alone and the co-pyrolysis of biomass with other raw materials.

Research on the Strategy of Film and Television Operation Management Mode

At this stage, with the rapid development of the film industry, more and more film and television works have emerged, mainly films, TV series, and online dramas. The film industry is an important part of the cultural industry of various countries. Analysing the operation mechanism of the film production management model will help the prosperity and development of the film industry. The research is mainly about the operation and management mode of the film and television industry. It uses the methods of searching for literature, searching on the Internet, and finally summarises the steps and strategies of film and television operation. The operation steps of film and television mainly include four links: shooting, production, distribution, and screening. Each link is quite important and needs to be carefully arranged and operated, with a strong team and psychological quality to deal with various emergencies. It must invest much money and energy in every step to complete perfect work and create profits in the final release. The operation of film and television is still advancing and will continue to develop new models and update strategies to meet the development of the times.

Predictive soil mapping using random forest models: Applications in pH and soil organic matter assessment

Digital Soil Mapping (DSM) presents a highly scalable and efficient alternative to traditional soil analysis, which is typically limited by its labor-intensive processes, time constraints and low spatial resolution. By utilizing advanced computational techniques such as machine learning and remote sensing, DSM overcomes these limitations and improves the accuracy, efficiency and scalability of soil property assessments. This study, conducted across Tamil Nadu, India, applied DSM and Random Forest (RF) models to predict 2 key soil properties: pH and Soil Organic Matter (SOM). We employed Conditioned Latin Hypercube Sampling (cLHS) for optimized sampling point selection and utilized the Boruta algorithm to identify the most relevant covariates for accurate modeling. The RF models were fine-tuned using a comprehensive grid search, with the optimal configuration spanning from 500 to 2000 trees (ntree) and mtry from 1 to 11. The best-performing model was found with 2000 trees and mtry set to 1 yielding superior prediction for SOM and pH with Root Mean Square Error (RMSE) values of 0.71 and 0.60 respectively, showcasing a high level of predictive accuracy. Our findings emphasize the critical role that remote sensing indices play in predicting SOM, while pH was influenced by both terrain features and remote sensing data. In comparison to previous studies, this research offers novel improvements in both sampling optimization and model configuration, leading to enhanced predictive performance. These results hold significant potential for sustainable land-use planning, agricultural productivity and environmental management.

Influence of rice straw incorporation and recommended dose of primary nutrients on growth, productivity and nutrient use efficiency of Rabi maize (Zea mays L.)

Rice-maize-based cropping system is one of the important agricultural practices in India. Maize has a wider range of adaptability to various climatic and soil conditions, which allows the farmers to cultivate the crop at various locations throughout the year. During the present days, straw handling after rice crop harvesting has become a major problem to the farmers and the burning of rice straw is considered as a serious environmental threat causing air pollution. In this scenario, incorporation of rice straw in succeeding maize cultivation can be beneficial in various aspects like soil health improvement, increased productivity and proper waste management. Considering these, the present field study was conducted at the Post Graduate Research Farm of Centurion University of Technology and Management, Gajapathi, Odisha, India. The experiment was laid out in randomized complete block design with 8 treatments and each treatment was replicated 4 times. The details of the treatment are as follows, T1: absolute control, T2: 100 % RDF, T3: 100 % RDF + rice straw incorporation (RSI) at 2 t/ha, T4: 100 % RDF + RSI at 4 t/ha, T5: 100 % RDF + RSI at 6 t/ha, T6: 100 % RDF + RSI at 8 t/ha, T7: 75 % RDF + RSI at 2 t/ha and T8: 75 % RDF + RSI at 4 t/ha. The experimental results found that the superior values of growth attributes were obtained highest in treatments T2: 100 % RDF, T3: 100 % RDF + RSI at 2 t/ha. Further, the incorporation of rice straw at the rate of 2 t/ha (T3) accounted for maximum grain yield (6354 kg/ha), stover yield (8429 kg/ha) and biological yield (14783 kg/ha) of maize and this treatment remained at par with T2: 100 % RDF. The experiment concludes that application of the optimum dose of fertilizers (100 % RDF) along with the incorporation of 2 t/ha of rice straw can be recommended for better growth, yield and nutrient use efficiency of Rabi maize.

Sustainable Management and Governance of Non-Wood Forest Products: Unlocking Their Potential

Forests are unique ecosystems that offer a vast array of ecosystem services, including non-wood forest products (NWFPs)—also known as wild forest products—that contribute to the wellbeing of societies worldwide [...]

Runoff Estimation in Kajurli Watershed Using SCS-CN and GIS Techniques

The study focuses on estimating surface runoff using the Soil Conservation Service Curve Number (SCS-CN) method, combined with Remote Sensing (RS) and Geographic Information System (GIS) techniques, for the Kajurli Watershed in Ratnagiri District, Maharashtra. Surface runoff is a key factor influencing agricultural productivity, soil erosion, and water management at the watershed level. The SCS-CN method, a widely used tool for runoff estimation, utilizes rainfall, land use, and soil type data. By integrating RS and GIS, the study achieves a more accurate assessment of land use and soil characteristics, which are critical inputs for runoff calculations. The Kajurli Watershed falls under hydrological soil group B, known for moderate runoff potential. The study uses 33 years of historical rainfall data (1990-2022) to compute annual runoff using the SCS-CN method. Key parameters such as Curve Numbers (CN) are derived based on land use, hydrological soil groups, and antecedent moisture conditions (AMC). The average annual rainfall in the watershed is found to be 3392.8 mm, with 39.69% of this rainfall contributing to surface runoff. The integration of RS and GIS simplifies spatial analysis, enabling accurate and efficient runoff estimation. The study highlights the sensitivity of the SCS-CN method to CN values, emphasizing the importance of precise land use and soil data for reliable hydrological modelling. These findings offer crucial insights for water resource management, flood control, and agricultural planning in the region.

The Effectiveness of Implementing a Milling Process in Reducing Production Process and Costs: A Case Study

Every product's design has a different process flow. Sometimes, designed products consist of a repeated process flow. Repeated processes are a problem that can affect production management and production output. This study has potentially proposed a new process that can replace the existing process by adding a milling process. The result shows that introducing a milling process was added to item 2 to produce a step slot and reduced the number of items used (Item 3). The assembly of Item 2 and Item 3 was converted into Item 6, which showcases a more substantial time differential, with the existing process taking 12.25 minutes and the new process requiring 0 minutes. The additional process of the new alternative milling machine reveals lower Watt, less time duration for the welding machine, reduced energy consumption for a hand-grinding machine, and lower cost demand for the welding machine than the existing process. In addition, the total cost of the added milling process shows a slight reduction in overall cost and is associated with energy consumption.

Crude Protein as an Indicator of Pasture Availability and Quality: A Validation of Two Complementary Sensors

This study evaluated the possibility of using two complementary electronic sensors (rising plate meter (RPM) and active optical sensor (AOS)) to obtain a global indicator, pasture crude protein (CP) in kg ha−1. This parameter simultaneously integrates two essential dimensions: pasture dry matter availability (dry matter (DM) in kg ha−1) measured by RPM, and pasture quality (measured by AOS), and supports management decisions, particularly those related to the stocking rates, supplementation, or rotation of animals between grazing parks. The experimental work was carried out on a dryland biodiverse and representative pasture, and consisted of sensor measurements, followed by the collection of a total of 144 pasture samples, distributed between three dates of the pasture vegetative cycle of 2023/2024 (Autumn—December 2023; Winter—February 2024; and Spring—May 2024). These samples were subjected to laboratory reference analysis to determine DM and CP. Sensor measurements (compressed height (HRPM) in the case of RPM, and normalized difference vegetation index (NDVI) in the case of AOS) and the results of reference laboratory analysis were used to develop prediction models. The best correlations between CP (kg ha−1) and “HRPM × NDVI” were obtained in the initial and intermediate phases of the cycle (autumn: R2 = 0.86 and LCC = 0.80; and Winter; R2 = 0.74 and LCC = 0.81). In the later phase of the cycle (spring), the accuracy of the forecasting model decreased dramatically (R2 = 0.28 and LCC = 0.42), a trend that accompanies the decrease in the pasture moisture content (PMC) and CP. The results of this study show not only the importance of extending the database to other pasture types in order to enhance the process of feed supplement determination, but also the potential for the research and development of proximal and remote sensing tools to support pasture monitoring and animal production management.

Governance of Village-Owned Enterprises in Promoting Economic Growth

background: The governance of Village-Owned Enterprises (BUMDes) plays a critical role in fostering sustainable development in rural areas. Specific background: This research explores the governance practices of BUMDes Kerto Emas, emphasizing the principles of transparency, cooperation, participation, and inclusiveness. Knowledge gap: Previous studies have not sufficiently examined how sustainable practices are implemented within the operational framework of BUMDes, especially concerning product management and website functionality. Aims: This study aims to assess the current governance indicators applied in BUMDes Kerto Emas, particularly regarding sustainability and the integration of digital platforms. Results: The findings reveal that while BUMDes Kerto Emas has made significant strides in governance, challenges remain in achieving sustainability, particularly in the underutilization of digital platforms for product display. Novelty: This study introduces a new perspective by linking sustainable business development with the need for improved online presence in village-owned enterprises. Implications: The research suggests that enhancing product offerings and optimizing digital platforms are essential for achieving long-term sustainability, providing a framework for improving governance in similar rural enterprises. Highlights : Governance principles must focus on transparency and cooperation for sustainable BUMDes operations. Digital platforms play a crucial role in enhancing product visibility and sustainability. Continuous evaluation is needed to optimize governance for long-term sustainability. Keywords: Governance, BUMDes, Sustainability, Participation, Digitalization

ЗАЛУЧЕННЯ ІНВЕСТОРІВ У ТЕРИТОРІАЛЬНОМУ МАРКЕТИНГУ

In the conditions of economic instability caused by the spread of the COVID-19 pandemic and military actions by the russian federation on our territory, local government authorities feel the impact of the "belt-tightening" strategy implemented by the central government. Faced with their own financial difficulties, the center reduces transfers, which were previously the main source of funds for supporting infrastructure and overall urban development. Therefore, territorial bodies aspiring to development must actively work on creating a positive image of their territory to diversify sources of capital and attract new investors. In this context, territorial marketing to attract investors is promotion (advertising). In turn, promotion is the fourth element of the implementation of territorial marketing, but it requires utilizing the entire marketing mix (the "4P" concept). When considering the first element of the implementation of territorial marketing, it is worth mentioning that many regions of our country can offer themselves to investors through so-called territories with preferential investment regimes. Thus, the task of forming the "territory for the investor" product will include two main components: the territory as a whole and territories with special regimes. To conduct pricing effectively, it is necessary to have a good understanding of investment projects and possess up-to-date information about the market. "Place" - location or placement - is the most complex and difficult concept in territorial marketing. While the placement of the territory cannot be controlled, the flow of resources passing through this territory, forming growth points, can be managed. Certainly, in business, promotion and advertising activities are more technologically advanced than in the public sector, but this is quite natural. There will be no significant differences because attracting a professional from the advertising market for government or local self-government is easier than a marketer working with the strategic block. However, if private practices and techniques are quite successful, more conceptual issues of promotion significantly lag behind. As in business, in territorial product management, it is advisable to use all available means, even if it is a small budget for advertising and a few exhibitions per year. However, marketing of territorial products, especially in attracting investors, is a complex task that is effectively solved comprehensively and sequentially, guided by the marketing mix.

Specific aspects of bacteriophage regulation: international practices and future developments

INTRODUCTION. The increasing prevalence of multidrug-resistant strains of pathogens determines the need for fundamentally new antibacterial agents, including bacteriophage preparations. The consistent implementation of phage therapy is hindered by the lack of generally accepted standardised regulatory documents governing the legal and methodological aspects of the production and preclinical and clinical studies of bacteriophage preparations.AIM. This study aimed to analyse the international experience with the production and lifecycle management of bacteriophage preparations, as well as the main regulatory requirements for the control of their quality, safety, and efficacy.DISCUSSION. It is difficult to develop virulent bacteriophage preparations in accordance with the existing requirements for other medicinal products because of the biological characteristics of bacteriophages, the wide variety of bacteriophage strains, and the potential for rapid changes both in the bacteriophage population and in the pathogen population. Therefore, it is reasonable to develop streamlined marketing authorisation routes for phage therapies and methods for the assessment of their safety and efficacy. As part of these efforts, it is necessary to assess the adverse events specific to this group of medicinal products, such as the risks of lysogeny, resistance to bacteriophages, and antibiotic resistance gene transfer between bacterial strains. The pharmaceutical development of bacteriophage preparations can be based on several approaches. Many countries worldwide, including the United States, are implementing the concept of Quality by Design, considering approaches based on the Biological Master File, and conducting Expanded Access programmes. The Active Substance Master File procedure allows the submission of a separate document package covering only part of the registration dossier for regulatory approval. Expanded Access programmes provide individual patients with access to innovative medicinal products without approved treatment protocols. In the Russian Federation, the commercial production of bacteriophage medicinal products is conducted in accordance with the quality standards specified in the State Pharmacopoeia of the Russian Federation.CONCLUSIONS. There are fundamental differences in the approaches to phage therapy and its regulation around the world and in the Russian Federation. It is reasonable to supplement the current national guidelines for the safety and efficacy evaluation of bacteriophage preparations, in particular, to specify the requirements for conducting preclinical studies.

Strategic digital product management: Nine approaches

Context:The role of product management (PM) is key for building, implementing and managing software-intensive systems. Whereas engineering is concerned with how to build systems, PM is concerned with ’what’ to build and ’why’ we should build the product. The role of PM is recognized as critical for the success of any product. However, few studies explore how the role of PM is changing due to recent trends that come with digitalization and digital transformation. Objectives:Although there is prominent research on PM, few studies explore how this role is changing due to the digital transformation of the software-intensive industry. In this paper, we study how trends such as DevOps and short feedback loops, data and artificial intelligence (AI), as well as the emergence of digital ecosystems, are changing current product management practices. Methods:This study employs a qualitative approach using multi-case study research as the method. For our research, we selected five case companies in the software-intensive systems domain. Through workshop sessions, frequent meetings and interviews, we explore how DevOps and short feedback loops, data and artificial intelligence (AI), and digital ecosystems challenge current PM practices. Results:Our study yielded an in-depth understanding of how digital transformation of the software-intensive systems industry is changing current PM practices. We present empirical results from workshops and from interviews in which case company representatives share their insights on how software, data and AI impact current PM practices. Based on these results, we present a framework organized along two dimensions, i.e. a certainty dimension and an approach dimension. The framework helps structure the approaches product managers can employ to select and prioritize development of new functionality. Contributions:The contribution of this paper is a framework for ’Strategic Digital Product Management’ (SDPM). The framework outlines nine approaches that product managers can employ to maximize the return on investment (RoI) of R&D using new digital technologies.

Economic optimization of sustainable soil management: a Dutch case study

Soil quality is pivotal for crop productivity and the environmental quality of agricultural ecosystems. Achieving sufficient yearly income and long-term farm continuity are key goals for farmers, making sustainable soil management an economic challenge. Existing bio-economic models often inadequately address soil quality. In this study, we apply the novel FARManalytics model, which integrates chemical, physical, and biological indicators of soil quality indicator, quantitative rules on how these indicators respond to farmers’ production management over time, and an economic calculation framework that accurately calculates the contribution of production management decisions towards farm income. This is the first study applying this model on existing arable farms. FARManalytics optimizes crop rotation design, cover crops, manure and fertilizer application and crop residue management. Nine Dutch arable farms were analyzed with a high variation in farm size, soil type, and cultivated crops. First, we assessed farm differences in soil quality and farm economics. Second, we optimized production management to maximize farm income while meeting soil quality targets using farm-specific scenarios. Third, we explored the impact of recent policy measures to preserve water quality and to increase the contribution of local protein production. The results show that the case farms already perform well regarding soil quality, with 75% of the soil quality indicators above critical levels. The main soil quality bottlenecks are subsoil compaction and soil organic matter input. We show that even in front-runner farms, bio-economic modeling with FARManalytics substantially improves economic performance while increasing soil quality. We found that farm income could be increased by up to €704 ha−1 year−1 while meeting soil quality targets. Additionally, we show that to anticipate on stricter water quality regulation and market shift for protein crops, FARManalytics is able to provide alternative production management strategies that ensure the highest farm income while preserving soil quality for a set of heterogenous farms.

Data analytics for working performance analysis in production management

RFID technology has found widespread application in supply chain processes. Previous research has primarily focused on managing products or stocks, with limited attention given to analysing workers’ performances through RFID data. This paper proposes a model for analysing employee performance using RFID data in production management. Key Performance Indicators (KPIs) are defined and utilised to process, analyse, and visualise the data through various analysis tools to develop the proposed model. Comparisons are conducted to evaluate employee performance between different groups based on the defined KPI. The model is validated by testing an independent data set, demonstrating its effectiveness in analysing existing data. Predictably, the model has the potential to reduce supervisory and associated costs in case-like applications.

Winter Wheat Yield Prediction Based on the ASTGNN Model Coupled with Multi-Source Data

Timely and accurate prediction of winter wheat yields, which is crucial for optimizing production management, maintaining supply–demand balance, and ensuring food security, depends on interactions among numerous factors, such as climate, surface characteristics, and soil quality. Despite the extensive application of deep learning models in this field, few studies have analyzed the effect of the large-scale geospatial characteristics of neighboring regions on crop yields. Therefore, we present an attention-based spatio-temporal Graph Neural Network (ASTGNN) model coupled with geospatial characteristics and multi-source data for improved accuracy of winter wheat yield estimation. The datasets used in this study included multiple types of remote sensing, meteorological, soil, crop yield, and planting area data for Anhui, China, from 2005 to 2020. The results showed that multi-source data led to higher prediction performance than single-source data, and enabled accurate prediction of winter wheat yields three months prior to harvest. Furthermore, the ASTGNN model provided better prediction performance than two traditional crop yield prediction models (R2 = 0.70, RMSE = 0.21 t/ha, MAE = 0.17 t/ha). Therefore, ASTGNN enhances the accuracy of crop yield prediction by incorporating geospatial characteristics. This research has implications for improving agricultural production management, promoting the development of digital agriculture, and addressing climate change in agriculture.

Developing manufacturing-relevant indicators for assessing long-run circularity of a product’s life cycle

The manufacturing industry holds a significant position in the U.S. economy, simultaneously contributing to a substantial share of energy and material usage, as well as environmental impacts. Developing manufacturing-relevant indicators will help decision-makers to understand the consequences of their decisions in terms of end-of-life (EoL) product management and promote the closing of loops within product life cycles. Nevertheless, indicators for assessing progress towards a circular economy for the manufacturing sector with respect to long-run behavior do not currently exist. To address this issue, this paper proposes two manufacturing-relevant indicators and their foundational methodology. These newly proposed indicators can capture the long-term behavior of a product’s life cycle and evaluate the associated circularity from both product and materials perspectives. Each scenario is presented to illustrate how these indicators could characterize the degree of circularity and its associated impacts for a given life cycle flow.