Profitable Business Model Research Articles

Historiography of Scientific Publishing across Cultures and Disciplines.

Historiography is a vital perspective of our scientific literature that charts the evolution of scientific publishing, from its early origins to the present status. The key transformations including the shift from a limited self-published legacy to specialized and professional peer-reviewed journals, the impact of technological advancements, and the emergence of new profitable business models are learning points for the future course and couture. Science is pursued and persevered by real humans in social and cultural contexts and not in isolation of laboratories or clinics. Survival of the impartial pure scientific bent of mind and its translation into tangible works has not been easy through the turmoil of various forms of force majeure. The lack of gender parity and even its divergence in some ways was palpable in the discourse of scientific research. Despite that, when provided with a common platform with comparable impact factors and rates of publications, gender inequality seems to vanish and equivalence in academia is discernible. The roles of authors, publishers, and readers have also evolved chronologically, adapting to the influence of cultural and disciplinary factors through the ages. The challenges of predatory publishing, open access, plagiarism, and data capitalization are also growing alongside. Ultimately, understanding the historical context and persistence of the predecessors in the course of scientific publishing can enhance modern scientific research and communication.

Innovative Approaches to E-Waste Management: Maximizing Metal Recovery and Sustainable Repurposing of PCB Waste

The global increase in electronic waste (e-waste) necessitates efficient recycling methods to mitigate environmental impact and recover valuable materials. This paper proposes two innovative methodologies for e-waste management, leveraging the strengths of both unorganized and organized sectors. The first method integrates collection, disassembly, and segregation by unorganized units with advanced metal recovery processes by professional recyclers, ensuring maximum yield and minimal environmental harm. The second method focuses on loosening components from PCBs using a combination of chemical and mechanical processes, followed by repurposing shredded PCB pieces into various decorative and household items. This dual approach aims to enhance sustainability, promote eco-friendly practices, and create a profitable business model for e-waste recycling.

Building blocks of change: The energy, health, and climate co-benefits of more efficient brickmaking in Bangladesh

The brick manufacturing industry in Bangladesh is characterized by informal inefficient coal-burning kilns that emit substantial greenhouse gases and air pollution. Despite decades of regulatory measures and the promotion of advanced kiln technologies, informal kilns persist. We employed a multiphase, interdisciplinary, mixed-methods approach to identify solutions. In this paper, we first summarize past approaches and discuss the key barriers we identified to improving the industry, then we present the design, and results of a randomized pilot energy efficiency intervention designed to overcome barriers to improved kiln operation. Our approach emphasized collaborating with informal zigzag kiln owners, who constitute the majority of brick producers, and carefully considering their incentives for changing a profitable business model. The intervention achieved high (60 %), including from non-study kilns, highlighting its appeal. Our findings provide insights into key elements for a successful intervention strategy that can be applied in larger-scale studies, not only for brick manufacturing but also for addressing broader environmental and health challenges.

Engineering Systems with Standards and Digital Models: Development of a 15288-SysML Grid

The paradigm shift that has spurred the fourth industrial revolution, in what is termed Industry 4.0, has ushered in the need to adopt digital technologies throughout the worldwide industrial base to support system design efforts. The adoption of digital technologies with a digital enterprise and the creation of cyber–physical systems are central tenets of Industry 4.0 and directly support profitable business models, improvements in efficiency, and ensure durable quality for the modern industrial base. However, the techniques for engineering systems require new, improved, digital life cycle process models if Industry 4.0—and the goals for its integrated systems—are to be realized. The development of a technique that improves the life cycles for systems within the digital enterprise is required. The 15288-SysML Grid described herein supports the Industry 4.0 paradigm and its associated digital enterprise. This is accomplished through (1) the application of a modern life cycle process model (i.e., the adapted diamond); (2) the utilization of international standards for systems; and (3) the adoption of the four fundamental aspects of system design supported by model-based systems engineering (MBSE) and the systems modeling language (SysML).

Enriching Carbon: Surplus Value Creation and Capture on the Voluntary Carbon Markets

AbstractThis article examines the creation and capture of surplus value in the voluntary carbon markets to show the importance of narratives and networks in justifying price. Rather than a push towards commensurability in carbon markets, it points to the emergence of profitable business models based on the enrichment of credits. Enrichment focuses not on processes of standardisation associated with commodity production, but on the creation of difference, uniqueness, and provenance. Drawing on ethnographic fieldwork and the marketing of a REDD+ project in San Martín, Peru, the article argues that the creation of surplus value in the voluntary market lies chiefly in the ability of vendors to create, manage, and sell narratives. A focus on the enrichment of carbon‐as‐an‐asset thus shows that narratives and networks go beyond performativity but are central to value construction, privileging certain actors and forms of labour and highlighting emerging forms of exploitation in green markets.

Leveraging New Business Models to Enhance Profitability in Cohort-Based Courses Edtech Businesses Study Case: PT Dibimbing Digital Indonesia

Over the past five years, the education technology (EdTech) sector has gained increasing prominence, characterized by significant growth in investments, transactions, and overall revenues. PT Dibimbing (Dibimbing.id), an EdTech company, experienced a decline in revenue largely attributed to elevated customer acquisition costs (CAC). This research aims to analyze the challenges faced by Dibimbing.id and form an innovative and profitable business model for Dibimbing.id. This study uses qualitative research by applying Richardson's framework theory (Value Oriented Framework). This research was obtained through in-depth interviews and Forum Group Discussions (FGDs). The FGD involved teams in Dibimbing.id, including marketing and sales, development, operations, human resources, finance, and technology teams. The results showed that the existing business model faces problems such as variable learning speed, highly complex learning syllabus, hiring difficulties to find advanced talents, bootcamp business model that does not contribute to profit growth, students' concerns with limited job prospects, and financial constraints. Therefore, four solutions were revealed in this research for a new business model, namely self-paced learning, leveling course, job guarantee program, and Study Now Pay Later (SNPL).

Peran Brand Awareness, Perceived Value, dan Brand Uniqueness dalam meningkatkan Brand Loyalty pada Industri Fast Fashion

Fast fashion is a term used to describe a highly profitable business model based on imitating catwalk trends and high fashion designs, and mass-producing them at a low cost. One of the famous fast fashion brands in Indonesia is XYZ. But in the past few years, XYZ’s brand value has decreased. The purpose of this research is to examine whether 1) brand awareness can influence brand loyalty. 2) perceived value can influence brand loyalty. 3) brand uniqueness can influence brand loyalty. Purposive sampling method used by distributing online questionnaire with a sample of 208 respondents and then processed by using smartPLS- SEM. The result of this study indicate that brand awareness, perceived value, and brand uniqueness have a positive and significant influence towards brand loyalty.

Scaling circular economy business models: A capability perspective

AbstractIn a context of growing environmental challenges, circular economy (CE) business models appear necessary for business to contribute positively to the ecological transition. While platform business models have been identified as a new and promising model in CE, we still lack a fine‐grained understanding of the critical capabilities involved in developing and scaling them. To fill this gap, we build on a single case study of Phenix, a French‐based fast‐growing start‐up in the food industry, tackling the issue of food waste. We identify three core managerial capabilities involved in the successful scaling of Phenix's business model. In addition to ecosystem orchestration capabilities, we identify two types of ambidextrous capabilities – forms of ambidexterity operating both at the organizational and at the institutional level. Our analysis highlights the importance of considering these capabilities in a bundle as they collectively contribute to the performance and scaling potential of the business model. We also call for an increased consideration of the role of institutional factors in shaping opportunities to design and scale profitable business models.

Vulnerability Assemblages: Situating Vulnerability in the Political Economy of Artificial Intelligence

“Vulnerability” is one of the terms recently used to discuss ethical aspects of artificial intelligence (AI). Current discussions on AI vulnerability tend to individualize vulnerability, largely neglecting its political dimensions, which are rooted in systems of inequality and disadvantage. This article draws on data from a multiple-perspective qualitative interview study to explore how notions of vulnerability underpin the development and implementation of AI. Results uncover how AI designers use narratives around missing data on vulnerable populations as justifications for the creation of synthetic data that were artificially manufactured rather than generated by real-world events. Although this was a profitable business model for AI companies, these practices ultimately situated long-term care residents as voiceless in the development of AI. This contribution shows how vulnerability is situated in a political economy of AI, which understands the absence of data on vulnerable groups as a possibility of profit creation rather than a chance of fostering inclusion.

Research on the Problems and Strategies of Live-Streaming E-commerce on the Douyin Platform in China

This paper analyzes the problems and challenges of live-streaming e-commerce on the Douyin platform in China. It focuses on product quality inconsistency, content homogeneity, and live-streaming regulation. It also suggests strategies to address these problems and challenges, such as using AI and QA to improve quality, focusing on innovation and differentiation to enhance experience, and establishing laws and standards to regulate behavior. The research significance of this paper lies in its contribution to the understanding and development of live-streaming e-commerce, a new form of online shopping that combines live video, social media, and e-commerce. Live-streaming e-commerce has become a popular and profitable business model in China, especially on the Douyin platform. By identifying and solving the problems and challenges of live-streaming e-commerce on the Douyin platform, this paper can help the platform, the live streamers, and the customers achieve better outcomes and benefits. However, this paper has some limitations, such as the lack of primary data from the participants. Therefore, future studies can use more direct and interactive methods to collect primary data from the stakeholders of live-streaming e-commerce on the Douyin platform. This can help to obtain more accurate and comprehensive information and insights.

Developing Capabilities for Sustainable Business Models –Exploring Project Maturity for Innovation Processes

Companies must cultivate new dynamic capabilities to meet the demands for sustainable solutions in an uncertain and dynamic world. This longitudinal case study explores the significance of project maturity as a critical capability within complex innovation processes for developing sustainable business models. The purpose of the study is to gain a better understanding of the central factors companies encounter when making efforts to build sustainable business models through innovation projects. Tracking a market-leading company's journey from ideation to implementation over an extended period, this study focuses on creating a sustainable business emphasising waste reduction, heightened customer satisfaction, and profitability. Key insights emerge through qualitative methods, including interviews, observations, and document analysis. 
 The findings highlight the pivotal role of project maturity in innovation projects centred around sustainable value propositions. Project maturity is salient in creating an autonomous unit, fostering agility, and promoting open collaboration. It encompasses organisational ambidexterity and collaborative engagement with vital stakeholders. Furthermore, proficient project managers well-versed in agile project management and innovation processes and contextual resolution emerge as crucial drivers in innovation projects aimed at developing capabilities for sustainable business models. By tailoring project maturity to the specific needs of each project and integrating agile methodologies, organisations can forge the necessary capabilities for crafting sustainable business models. Additionally, dynamic capabilities can be cultivated by aligning projects with the overall business strategy and implementing practices that facilitate continuous learning and improvement. 
 This study underscores the importance of project maturity within innovation processes and its role in creating profitable and sustainable business models by developing new dynamic capabilities. The research findings offer valuable insights for businesses seeking to design effective innovation processes supporting sustainable business model realization.

Digital information management to increase the reuse of building materials

The construction industry contributes significantly to global greenhouse gas emissions and extraction of primary resources. The linear economy models used in building development projects are unsustainable. Hence, implementing circular economy models in the building development process is necessary. This paper aims to increase reuse in building projects. The study utilized a literature study, 18 interviews with construction industry professionals, and two case studies. The focus of the study was the role of digital information management in achieving a circular economy and a narrowed scope on the reuse of building materials and components. The results show six challenges for increasing the reuse of building materials in construction projects. The most central challenges are profitability, human willingness to action and change, and storage of reusable building materials. Based on the findings in this paper, a framework is developed for how digital information of construction resources can be utilized and managed throughout the lifetime of buildings. The suggested solutions will enhance the ability of property owners and developers to achieve circularity in their building projects and existing building stocks. In this respect, this paper contributes to the emergence of new profitable business models and markets within a circular value chain for building materials in the construction industry.

Analyze IMDb movies by sentiment and topic analysis

Movie is an important cultural form, carrying multiple levels and meanings such as art, entertainment and social value. Movie review and rating data sets are huge, and deep learning and natural language processing methods are widely used today. Advances in big data and deep learning offer unprecedented opportunities to understand moviegoer behavior and preferences while providing a cost-effective way to gain insights relevant to the entertainment industry. This project conducts sentiment analysis, topic modeling, and visual statistical analysis based on the IMDb movie data set to identify key factors and deeper insights that influence successful decision-making in film production. This project first uses the word embedding method to vectorize the movie review text, and then uses Bidirectional Long Short-Term Memory (Bi-LSTM) to perform sentiment classification. In addition, statistical methods such as visualization were used to discover conclusions such as the highest average number of movies released in November, and identify trends, patterns and relationships between the variables of IMDb movies. Finally, the Latent Dirichlet Allocation (LDA) topic modeling model was constructed to find out that the important topic with increased demand is light entertainment movies, highlighting the commercial feasibility of comedy movies as a profitable business model. In summary, this project uses an emotion-topic fusion analysis method based on the Bi-LSTM emotion classification method and the LDA topic modeling method. The results show that the Bi-LSTM model can better identify positive and negative emotions in movie reviews, and the LDA topic model performs well in mining popular topics.

Is it wise to compete or to collaborate? Remanufacturing business models under collective extended producer responsibility legislation

Collective extended producer responsibility (CPR) legislation aims to accomplish manufacturers’ extended producer responsibility (EPR) through a common channel of product recovery activities. This work intends to study the impact of the CPR legislation system on competitive and collaborative business models of original equipment manufacturers (OEMs) and independent remanufacturers (IRs). Therein, we developed a two-period competitive and collaborative model considering an oligopoly market scenario for analysing optimal remanufacturing and pricing strategies of OEMs and IRs. Government subsidies promote the remanufacturing activities, and their effects are examined on optimal remanufacturing and pricing decisions for competitive and collaborative models under CPR legislation. The result highlights that competition with IRs under the CPR legislation system within oligopoly market scenarios is profitable for OEMs. Furthermore, the result indicates that a competitive business model increases consumer surplus, increasing used products collection and remanufacturing. The findings benefit OEMs of identical products from implementing a profitable business model under CPR legislation to restrict the availability of low-quality remanufactured products of IRs, thereby protecting the brand image and controlling the cannibalization effect on new products selling.

Rapid Estimation of Battery Storage Capacity through Multiple Linear Regression

Due to global warming issues, the rapid growth of electric vehicle sales is fully expected to result in a dramatic increase in returned batteries after the first use. Naturally, industries have shown great interest in establishing business models for retired battery reuse and recycling. However, they still have many challenges, such as high costs from the logistics of returned batteries and evaluating returned battery quality. One of the most important characteristics of a returned battery is the battery storage capacity. Conventionally, the battery’s energy capacity is measured through the low current full charging and discharging process. While this traditional measurement procedure gives a reliable estimate of battery storage capacity, the time required for a reliable estimate is unacceptably long to support profitable business models. In this paper, we propose a new algorithm to estimate battery storage capacity that can dramatically reduce the time for estimation through the partial discharging process. To demonstrate the applicability of the proposed algorithm, cylindrical and prismatic cells were used in the experiments. Initially, five indicators were selected from the voltage response curves that can identify battery storage capacity. Then, the five indicators were applied to principal component analysis (PCA) to extract dominant factors. The extracted factors were applied to a multiple linear regression model to produce a reliable estimation of battery storage capacity.

Legal Evaluation of Franchise Business Contracts Using Civil Law

This study was conducted in order to learn more about the characteristics of the franchise industry and how its development relates to the rapid development of the franchise industry in Indonesia. According to the findings of the study, the franchise industry is still largely unknown among Indonesians even though it is a more profitable and capital-efficient business model than starting a new business. With certain rights and obligations carried out by each party based on the terms of the agreement set forth in the Civil Code, this franchise business can be launched immediately after an agreement is reached between the owner of the franchise right and the holder of the franchise right. franchise rights. However, apart from the basic contractual terms, the government-specific laws and regulations that serve as the legal framework for the growth of this franchise business are still very inadequate. As a result, many entrepreneurs continue to be "afraid" of starting this kind of business and instead prefer to build their own.

Accounting and analytical support for investment attractiveness evaluation of high-growth companies

Subject. The article addresses analytical support for assessing the investment attractiveness of fast-growing companies as a driver of economic growth of the national economy. Objectives. The purpose is to identify optimal investment objects among fast-growing companies through the tools of economic analysis. Methods. The study employs general scientific methods of research, like analysis, comparison, interpretation, and economic and statistical methods. Results. The paper defines the concept of a "fast-growing company", considers the evolution of this economic phenomenon and key works of domestic and foreign scientists that popularized the term, underpins the importance of fast-growing companies for increasing the economic growth rates of an individual State. We reviewed the key challenges faced by fast-growing companies in conditions of global economic uncertainty caused by political instability, described the tools used by advanced companies to mitigate economic risks within their adaptive development strategy. In the context of the analysis of investment attractiveness, we focused on the dynamics of three groups of indicators: profitability, financial stability and efficiency. Conclusions. Based on analyzed coefficients, we conclude that there are certain internal difficulties in some fast-growing companies, which reduce their investment appeal. The assigned rating of a fast-growing company does not always imply the most profitable and efficient business model. To determine the investment attractiveness of companies, additional research would be needed.

Development and evaluation of Artificial Intelligence techniques for IoT data quality assessment and curation

Nowadays, data is becoming the new fuel for economic wealth and creation of novel and profitable business models. Multitude of technologies are contributing to an abundance of information sources which are already the baseline for multi-millionaire services and applications. Internet of Things (IoT), is probably the most representative one. However, for an economy of data to actually flourish there are still several critical challenges that have to be overcome. Among them, data quality can become an issue when data come from heterogeneous sources or have different formats, standards and scale. Improving data quality is of utmost importance for any domain since data are the basis for any decision-making system and decisions will not be accurate if they are based on inadequate low-quality data. In this paper we are presenting a solution for assessing several quality dimensions of IoT data streams as they are generated. Additionally, the solution described in the paper actually improves the quality of data streams by curating them through the application of Artificial Intelligence techniques. The approach followed in our work has been to append data quality information as metadata linked to each individual piece of curated data. We have leveraged linked-data principles and integrated the developed AI-based IoT data curation mechanisms within a Data Enrichment Toolchain (DET) that employs the NGSI-LD standard to harmonize and enrich heterogeneous data sources. Furthermore, we have evaluated our design under experimental research conditions, achieving a robust compromise between functionality and overhead. Besides, it demonstrates a stable and scalable performance.

Innovative Business Models for the Future Smart City

This paper examines how to outline and adopt innovative business models for the Smart Cities of the future. Smart Cities are intelligent and efficient communities and ecosystems employing digital technologies to respond a growing waste of resources, unsustainable environmental impact, and inefficiency in traditional processes. Considering the greatest benefits of Smart Cities on economies, societies, and environment, many countries have now introduced national Smart City projects in order to transform life, improve business operations and market competitiveness. However, despite growing interests towards Smart Cities, it remains still difficult to adopt this paradigm due to digital transformation, interaction strategies, social and cultural problems. Therefore, this paper aims to break down the barriers to these problems and support the literature and management to understand how to implement profitable business models for Smart Cities of the future. Specifically, we identify four main areas characterizing Smart Cities (i.e., Smart Mobility, Smart Living, Smart Energy, and Smart Public Ecosystems) where digital technologies have shown greater progress with large savings. For each area, multiple case studies have been discussed and Business Model Canvases have been developed for generalizing effective methodological approaches toward efficient implementation of Smart City paradigm. Results are threefold. As for digital transformation problems, we show how digital technologies (e.g., Cloud, IoT, Big Data and AI) are applied profitably through innovative business models; as for interaction strategies problems we indicate how to organize innovative ecosystems involving public and private actors to promote Smart Cities; as for social and cultural problems we delineate change management and communication practices useful to instill in all stakeholders a culture towards the Smart City. With these findings the paper aims at enriching scientific knowledge about the Smart City Paradigm by means of a business model perspective and to offer public administrations insightful guidelines for the transition toward Smart Cities.

Karakteristike i uslovi razvoja digitalnih hartija od vrednosti na globalnom i nacionalnom tržištu kapitala

We are witnessing the transformation of the financial instruments industry and the processes taking place in the capital market, which have initiated a new trend in securities business. The contemporary progress of the global digital securities market is characterized by interactions between rapid technological innovations, changes in investor habits and competition among technology giants. The research subject is supported by the fact that digital securities offering becomes a profitable business model available on blockchain platform, making securities the most interesting financial instruments in the 21st century. The aim of the research is to overview characteristics of digital financial instruments as a consequence of the difference in territorial areas and legislation, as well as how this affects the potential and challenges of development in the capital market. Description method, analysis and synthesis technique, as well as the documents content analysis in the relevant area, were used for the purposes of the research. The result of the research confirms further development of digital securities in a very challenging environment and resources mobilization through alternative funding methods.