Business Tool Research Articles

Conceptual Metaphor BUSINESS IS A JOURNEY in Business Terminology

Departing from the conventional understanding that metaphor is merely a component of rhetorical and poetic expression, the Theory of Conceptual Metaphor provides linguistic evidence that metaphor plays a crucial role in creating new specialized vocabulary. The present study attempts to apply the Conceptual Metaphor Theory to analyze the metaphor BUSINESS IS A JOURNEY in nominating business terminology. The corpus of the study comprises 179 metaphorical business terms collected from business dictionaries and textbooks. It is discovered in the study that certain attributes of the “journey” source domain are mapped onto those of the “business” target domain, resulting in four derivative metaphors in business terms, namely companies are conventionally viewed as travelers, business tools are metaphorically described as vehicles, business growth is conceptually viewed as the roadmap and distance covered, and business challenges are metaphorically described as obstacles encountered. The research findings highlight metaphorization as an effective method of business term nomination.

Factors Influencing the Career Advancement of Malaysian Women Homepreneurs on the TikTok Platform

Entrepreneurship significantly contributes to economic growth, with recent studies highlighting the rise of female entrepreneurs who challenge traditional business roles by becoming "homepreneurs." The current research focuses on Malaysian women homepreneurs using TikTok, a platform that has transformed from entertainment to a vital business tool, facilitating unique career advancement opportunities. This study aims to explore the impact of digital marketing skills, product quality, customer engagement, and understanding of TikTok's algorithm on the career advancement of Malaysian women homepreneurs. In the quantitative study focusing on the career advancement of Malaysian women homepreneurs using TikTok, the methodology incorporated structured questionnaires to assess the relationships between key variables. The data was collected from 400 participants via Google Forms, leveraging a purposive sampling technique to ensure a representative sample of women homepreneurs active on TikTok. The statistical analysis revealed that while digital marketing skills and customer engagement did not significantly impact career advancement on TikTok, a thorough understanding of the platform's algorithm was strongly associated with career progression. Conversely, the results indicate that product quality was negatively significant in driving career advancement for Malaysian women homepreneurs on TikTok. This study highlights the need for targeted strategies focusing on product excellence and deep comprehension of platform algorithms to effectively leverage TikTok for career development.

The Multifaceted Role of Social Finance in Supporting Social Entrepreneurship: A Qualitative Inquiry into Business Tools and Value-Adding and Subtracting Activities

Social finance (SF) may be in a good position to provide the resources impact-driven ventures (IDVs) need to effectively innovate and scale. However, little is known about the way SF experts conceptualise and align the resources they provide to IDVs. In this paper we investigate (1) the tools SF experts apply to guide business model development of their investees and (2) the activities they perceive as value-adding or value-subtracting. Findings suggest that different strategies for business model advice are adopted, reflecting a spectrum of investor involvement levels, and that a wide range of activities have the potential to either add significant value to IDVs or detract them from their goals.

The Impact of Mergers and Acquisitions on Technological Innovation of Enterprises: Taking Apple as an Example

As market competition becomes increasingly fierce, in order to maintain a leading position in the industry, companies must enhance their core competitiveness to gain priority discourse power in the market. Corporate mergers and acquisitions are the act of acquiring property rights of other legal entities through certain economic means on the basis of equality, voluntariness, and equal compensation. They are a major form of capital operation and management for enterprises. This article aims to study the impact of mergers and acquisitions on technological innovation in enterprises, by analyzing the financial statements of enterprises and exploring the impact of mergers and acquisitions on their main business. Research has found that mergers and acquisitions are a business tool that can effectively enhance a company's technological level without increasing profits, while using less time cost. This provides a reference for enterprises to enhance their market competitiveness, differentiate their products, and adjust their business strategies.

UPAYA PENINGKATAN NILAI EKONOMIS PRODUK UMKM MELALUI SOSIALISASI BISNIS DIGITAL DI DESA CILANGKARA

Technological developments, especially in digital business, have had a positive impact on Micro, Small and Medium Enterprises (MSMEs) in rural areas, such as Cilangkara Village. Even though the growth trend of internet users in Indonesia shows a significant increase, observations and interviews show that the majority of village residents have not shown sufficient interest in entrepreneurship, especially in facing current developments. In this context, the community service program by Islamic University 45 Bekasi students aims to provide education and increase village residents' interest and skills in entrepreneurship, especially by implementing digital business. Implementation methods, such as observation, outreach and training, are expected to stimulate interest and provide support to village residents, including providing business tools to MSMEs that are not yet running. Digital business education is the key to increasing the competitiveness of MSMEs and driving economic potential at the local level, as is being pursued through community service activities in Cilangkara Village. The latest evaluation shows an improvement in the quality of life of the community, especially among MSMEs in Cilangkara Village, through increasing operational capabilities of digital applications for analysis, marketing and product production. It is hoped that the success of this program will be a sustainable first step to improve and produce MSMEs that are able to compete and develop along with the times.

A Comprehensive Taxonomy of Modern Public Cloud Services for Infrastructure Selection

The rapid adoption of public cloud services has transformed the digital landscape, offering diverse solutions to meet different business needs. However, this diversity of services also presents a challenge: the need for a structured, comprehensive taxonomy to navigate and understand the offerings. This paper presents a comprehensive taxonomy for public cloud services, aiming to provide clarity and structure in this domain. Leveraging extensive market research, analysis of leading industry reports, and insights from top cloud vendors, we have identified key criteria that form the foundation of our taxonomy. The taxonomy passed the validation process, involving industry experts from Ukraine's largest telco operator, ensuring its practical relevance. The results have proven the taxonomy's effectiveness in classifying a wide range of cloud services, highlighting its potential as a valuable tool for businesses, researchers, and cloud practitioners. This research serves as a foundation for future improvement of complex processes of cloud provider selection.

Social Media Utilization of Microbusinesses in A Component City in Northern Philippines

Social media has become an essential marketing and communication tool for businesses of all sizes, offering opportunities to engage with customers and promote products in a cost-effective manner. This study explored the use of social media by microbusinesses in a component city in the Northern Philippines, focusing on the platforms used, reasons for adoption, benefits gained, and challenges encountered. A qualitative approach was employed, and 30 microbusiness owners from the service, merchandizing, and manufacturing sectors were selected through quota sampling. Data were collected using an interview guide and analyzed using Braun and Clarke’s Thematic Analysis. The results show that Facebook was the most widely used platform, followed by Instagram and TikTok. The primary reason for using social media was to promote products and services. Benefits include wider market reach, increased sales, and improved communication. However, challenges such as market competition and time management difficulties were identified. Despite these hurdles, social media has proved to be a vital tool for business continuity, particularly during a pandemic. The study highlighted the critical role of social media in supporting the growth and sustainability of microbusinesses and recommended further research to explore other social media platforms and business sizes.

Machine Learning-based Human Resource Management Information Retrieval and Classification Algorithm

Efficient human resource management (HRM) is essential for company achievement in today’s fast-paced corporate world. Businesses must find effective ways to retrieve and categorise the ever-growing amount of HR-related knowledge. This work presents a new method for retrieving and classifying HRM data using machine learning. Modern natural language processing (NLP) and CNN methods are used by the algorithm we developed to handle unorganized human resources (HR) information, including worker records, job postings, and certificates. HR decision-making is facilitated by the system’s ability to derive insightful information from the information using sophisticated text mining and machine learning algorithms.The two main parts of the method are classification and data extraction. HR workers can more easily obtain the required knowledge thanks to information retrieval, which makes it possible to search HR data quickly and accurately. Contrarily, categorisation optimises the division of human resources information into pertinent classifications, including job positions, competencies, and achievement grades. We assess our algorithm’s effectiveness on various datasets from actual HR datasets. The outcomes show how well our strategy works to streamline HRM procedures, cut down on manual labour, and increase the precision of decisions. Furthermore, our technology is compatible with corporate human resources offices and educational settings because it complies with worldwide university requirements.This study belongs to the growing body of knowledge in HRM. It provides a useful tool for businesses looking to improve employee relations, simplify HR procedures, and attract and retain talent. The suggested method is a valuable resource for academics and businesses alike because of its versatility and compliance with global educational norms.

The Impact of CRM Systems on Customer Satisfaction and Retention

Customer Relationship Management (CRM) systems have become essential tools for businesses aiming to enhance customer satisfaction and retention. This research investigates the impact of CRM systems on these critical business outcomes by analyzing data from various companies that have implemented CRM solutions. The study explores how CRM systems facilitate improved customer interactions, personalized services, and efficient problem resolution. Our findings indicate that businesses utilizing CRM systems experience significant improvements in customer satisfaction and retention rates. The research also highlights key factors that contribute to the successful implementation and utilization of CRM systems, including employee training, data quality, and technological integration. These insights provide valuable guidance for organizations seeking to leverage CRM systems to foster stronger customer relationships and achieve sustainable growth.

Breakage analysis for profitability management in high-value, low-frequency loyalty programs

Loyalty programs (LPs) have become crucial tools for businesses seeking to cultivate customer relationships while maintaining profitability. Among the important factors influencing the profitability of LPs is the expiration of points, especially for high-value, low-frequency (HVLF) programs with high financial liabilities. While expiration induces complex dynamics, its long-term effect has been underresearched in the literature. Point expiration can incentivize point redemption and purchases but may affect customer engagement. Thus, determining the overall long-term impact of expiration on profitability is challenging. To evaluate the role of expiration in the profitability of an LP, managers carefully monitor breakage, which corresponds to the fraction of accrued reward points that expire before being redeemed. Although breakage provides a succinct indicator of the impact of point expiration in the long term, its estimation presents several challenges associated with the projection of customer behavior over a long period of time. In this research, we propose a new methodology for estimating breakage, which can assist businesses in making informed decisions regarding the design of their LPs. Our proposal considers models of point redemption and purchases and a detailed description of point expiration according to the internal rules of the program. We apply our methodology to a large regional airline and find that (1) our approach provides better recovery of the breakage than other metrics used in the industry, (2) there are significant variations in the estimated breakage among customers and across markets, (3) customer heterogeneity and dynamics are important for calculating long-term metrics, (4) expiration can be quite inelastic to some strategies commonly used in the industry to equalize breakage, and (5) to decrease the breakage rate, it is more effective to promote more frequent redemptions than to favor rewards that require a greater number of points.

PECULIARITIES OF MARKETING AND BRANDING IN THE CONFECTIONERY AND CAFE INDUSTRY

The purpose of this article is to determine the essence and theoretical features of marketing and branding in the confectionery and cafe industry, as well as the challenges associated with marketing activities in these establishments. The main research methods used in the article include induction, synthesis, analysis, comparison, and generalization. The specific features of marketing activities in confectioneries and cafes have been identified. The impact of marketing efforts on service delivery in these establishments has been studied. Key problems arising from marketing activities and brand promotion in confectioneries and cafes have been identified. Various tools used in marketing efforts within this industry, which constitute the marketing mix or marketing complex, have been explored. The peculiarities of developing a marketing plan for confectioneries and cafes using the “5R+1C” integrated marketing model, and elements of the marketing mix specific to the food industry, are discussed. The ecosystem of the internet marketing strategy for confectioneries and cafes is outlined. The necessity for increasing social media activity (SMM) and enhancing market recognition, as well as developing a user-friendly website with online table reservations and sweet order functionalities, has been emphasized. Directions for optimizing the digital strategy effectiveness for confectioneries and cafes, focused on improving brand recognition among target audiences, are proposed. Factors influencing the selection of Google’s contextual media network for the promotion of confectioneries and cafes are outlined. The required changes for social media pages and websites to enhance brand promotion are discussed. International experiences regarding the efficacy of business tools in the food industry, incorporating marketing concepts, are also explored. The main idea of advertising campaigns, centered around creating favorable conditions for customer purchases and replicating the brand’s style in every part of the establishment, is reviewed. The specifics of consumer loyalty, shaped by the brand’s appearance, communication, establishment design, and available offerings, are also examined.

Optimalisasi Media Sosial Youtube sebagai Media Berwirausaha

YouTube is a website that allows people to upload and exchange videos. YouTube is an effective social media platform for companies to introduce their products through video content. YouTube is developing into an effective tool for business. YouTube offers live broadcasts of product or service demos, YouTubers can record and post videos about the offers they want, and these offers can attract clients. With millions of videos produced every day, YouTube social media has a good chance of getting videos seen, so you have the opportunity to succeed in online business using YouTube media. Another advantage of social media is that YouTube can improve their marketing techniques and gain a better understanding of their audience by using the analytical tools that YouTube offers. Therefore, YouTube serves as an important tool for doing business online, besides being a place to share YouTube videos. Considering the background information provided, optimizing YouTube social media aims to motivate and improve the abilities of Dawis mothers who want or are currently entrepreneurship in utilizing YouTube as an online business medium. Mrs. Dawis can improve viewers' understanding and retention of knowledge by producing more visually interesting informational material or videos on YouTube. People are more likely to understand and retain knowledge when it is presented on YouTube in an original and engaging way. Therefore, optimizing social media is needed to help Dawis mothers develop their capacity to produce interesting and successful YouTube videos. Thus, Dawis women can use YouTube as a platform for online commerce and entrepreneurship more effectively. This community service aims to optimize the use of YouTube social media as an entrepreneurial tool for Dasa Wisma (Dawis) women in Amposari Village, Pedurungan District, Semarang City. This program was implemented by the Community Service (PKM) team from the Muhammadiyah Semarang Institute of Statistics and Business Technology in March 2024. This activity included theoretical and practical training involving 25 participants from various RTs in the village. The methods used include interviews, discussions, lectures, and questions and answers, with the aim of exploring online business ideas and improving the entrepreneurial spirit of participants

The Possibilities of Artificial Intelligence Usage in Loyalty Programs

From the year 2022, when the GPT 3 model became publicly available, Artificial intelligence (AI) has been a buzzword in marketing. To say it still is influencing the field would be an understatement with new models and technologies continuously emerging and existing ones getting better and better. Loyalty programs as a sales promotion tool have also undergone big changes in recent years and AI is bringing new opportunities and challenges to the field. In this paper, we investigate the possibilities of artificial intelligence usage in loyalty programs. We aim to showcase the diverse opportunities through which AI can enhance loyalty program experiences. Among those usage opportunities we put specific attention on AI personalization and predictive modelling. By harnessing AI capabilities, organizations can possibly find new ways to enhance customer engagement, satisfaction, and build stronger loyalty. In this paper we are also looking at the current state of loyalty programs in the selected market and the way AI is being used in them. It is important to note that we approach the topic from two points of view – customers` and brands`. That means that we are trying to highlight how certain AI technologies can possibly improve customers` experience as well as how AI may be a helpful tool for businesses who want to manage loyalty programs. The final part of our article includes information on the suggested ways AI technologies may be implemented into loyalty programs based on the information provided in previous parts of the paper. Suggested implementation strategies are also appropriate as a starting point for further research, where every single technology would be researched more in detail. The main goal of this article is to provide readers with a comprehensive overview of the possibilities of how Artificial Intelligence can be used in the context of loyalty programs today. The article is theoretical-empirical and is based on external information from trustworthy sources as well as our own research of certain AI technologies in the context of loyalty programs.

Innovative Content Production in Marketing Communication Through AI

The integration of artificial intelligence (AI) into marketing communications has changed the way businesses communicate with their customers. The present paper explores the potential of AI-driven systems to automate content creation, highlighting the role of AI in increasing customer engagement and strategic decision making. AI offers significant benefits by leveraging customer data to predict their behaviour, optimize marketing strategies, and personalize content. By systematically creating and evaluating content, AI enables marketers to customize messages to specific audiences, increasing the effectiveness of campaigns. The research employs a mixed methods approach that combines qualitative and quantitative analyses to assess the potential use of AI in content marketing. The qualitative aspect involves a thorough review of existing literature, identifying key trends and relationships in the use of AI for marketing communications. On the other hand, the quantitative aspect of the study involves a process of experimental validation using Python and APIs such as OpenAI and Graph APIs to automate content creation and measure its effectiveness. The findings confirm that AI can be utilized to personalize content using the input data in the form of brand-voice, target group, and the evaluation of current communication. The iterative process allows for continuous improvement of quality and relevance of content, which is important in the dynamic environment of marketing communications. The study highlights the importance of accurately defining the target audience and brand-voice, as the effectiveness of AI depends heavily on the accuracy of the input data. However, the study also acknowledges limitations such as the potential inconsistency of the content generated through AI and the challenges associated with maintaining a coherent brand-voice. Future research should focus on developing advanced machine learning methods to better understand context and improve the alignment of content with brand values and customer expectations. In conclusion, the integration of AI into marketing communications offers a powerful tool for businesses to optimize content creation, increase customer engagement, and achieve strategic goals in an increasingly competitive digital environment. AI's ability to create, evaluate and refine content in real-time provides a significant advantage and ensures that marketing communications remain adaptive and effective.

Pengaruh Bahasa Indonesia sebagai Alat Komunikasi dalam Bisnis Internasional di Era Digital

This article examines the role of Indonesian as a communication tool in international business in the digital era. This topic is important given Indonesia's economic growth and its potential in the global market, particularly in Southeast Asia. The research uses a literature review method, analyzing relevant sources related to the use of Indonesian in the context of international business. Opportunities that can be leveraged include the growth of e-commerce and the potential of Indonesian as a lingua franca in Southeast Asia. The study concludes that with the right strategies, Indonesian can become an effective communication tool in international business, opening opportunities for Indonesian companies in the global market and helping foreign companies adapt to the Indonesian market.

Investigating the Evolution of Cloud Computing: Research Perspectives

Cloud computing is an economical and powerful tool for small businesses, especially in developing countries. It offers a scalable solution for enterprise resource planning, supply chain management, customer relationship management, healthcare applications, and mobile apps that can reach many users. In this paper, we examine the various concepts associated with cloud computing. Leveraging our experience with different clouds, we explore clouds from technical and business perspectives. We highlight some of the opportunities in cloud computing, emphasizing the importance of cloud technology. This paper provides detailed information about the features, uses, and practical applications of cloud computing.

Circular-ESG Model for Regenerative Transition

This paper presents a novel circular-ESG framework integrating circular economy (CE) principles with environmental, social, and governance (ESG) criteria to address the lack of uniform sustainability measures. We introduce normalized sustainability coordinates (NSCs) as a comprehensive metric for sustainability performance, reconciling economic development with environmental balance. The circular-ESG model employs a four-quadrant Cartesian system to map business model impacts on natural and socio-economic systems, ranging from linear open-loop to circular closed-loop ESG models. This framework enables empirical analysis through data-driven NSCs (−1 to 1) and establishes temporal key performance indicators. By incorporating the Human Development Index within ecological limits, the model promotes regenerative development aligned with planetary boundaries. The circular-ESG approach offers a practical tool for businesses, households, organizations, and policymakers to navigate sustainable development complexities. This integrated framework fosters innovation and supports a just transition towards regenerative practices, providing a roadmap for high human development within ecological limits. The circular-ESG model advances sustainability science and management, contributing to the discourse on measuring and implementing sustainable practices across sectors and scales. The model is currently conceptual; we encourage empirical validation and further research to explore its practical applications and effectiveness in real-world scenarios. While the provided examples of use cases serve as conceptual demonstrations, future research could empirically apply the model to real-world data.

Enhancing customer service and user experience through the use of machine learning powered intelligent chatbots

The implementation of machine learning powered intelligent chatbots have greatly enhanced customer service and user experience in various industries. With the advancements in artificial intelligence and natural language processing, chatbots have become an essential tool for businesses to effectively communicate with their customers. Machine learning algorithms enable chatbots to analyze customer queries and provide accurate responses, mimicking human conversation. This has led to an increase in customer satisfaction as chatbots can handle large volumes of inquiries and resolve them efficiently. Moreover, chatbots are available 24/7, providing round-the-clock service to customers. Implementing chatbots in businesses has also resulted in cost savings as they reduce the need for human customer service representatives. This has allowed companies to allocate their resources to other areas of their business, ultimately leading to increased productivity. In addition to improved customer service, intelligent chatbots also enhance user experience. By continuously learning from user interactions, chatbots can personalize responses and provide relevant information, making the customer experience more seamless and efficient. Furthermore, chatbots can be integrated into various platforms such as websites, social media, and messaging applications, making them easily accessible to users. This has also led to an increase in user engagement and retention rates. The potential challenges and limitations of this technology was also discussed and recommendations provided for future research in this field. Overall, the development and implementation of machine learning powered intelligent chatbots have greatly enhanced customer service and user experience, making it a valuable tool for businesses in today's digital age.

British consumer perspectives on terroir in cheese

PurposeThis paper reports on a project looking at consumer perceptions of terroir in the UK, using cheese as a stimulus for the data collection.Design/methodology/approachData collection was based on a consumer survey using a discrete choice experiment which included a number of cues to, and stories about, terroir. Analysis of preferences produced three latent classes with varying attitudes towards terroir cues for cheese. There was also an open-ended question giving rise to a qualitative analysis of respondents understanding of the work “terroir”.FindingsWhen faced with the terroir cues most used some positively to make their choices. A PDO label and stories about the production region and method and business structure all generally offered positive utility.Originality/valueTerroir is a widely used term in the marketing of (especially) wine, particularly in Europe, offering a form of authenticity and has been very important in policies to sustain the economies of otherwise declining rural areas. It has been adopted by producers in the English-speaking world but is less widely recognised, by consumers. The significance of this study is that it is the first large-scale survey of British consumer perceptions around a key tool for rural businesses – terroir – and one of the first around a non-wine product, and it explores the stories which resonate most effectively with consumers.

Sentiment Analysis of Arab Tweets: Unveiling Public Opinion Trends Using Machine Learning

Abstract: The rapid spread of social media platforms, especially Twitter, has provided a rich and valuable source of data for understanding public opinion. This thesis presents a comprehensive study on analyzing the sentiments of Arab tweeters, intending to reveal public opinion trends using advanced machine learning techniques. The study begins by collecting a large data set of tweets in Arabic. Preprocessing steps are carefully implemented to deal with the unique linguistic characteristics of Arabic, including encoding, normalization, and deletion. The BERT system was used for the application and the model was created using AJGT.csv Dataset. The evaluation was performed using different metrics. The test results were as follows: 0.9822 % accuracy, precision 0.9823, recall 0.9822, F1 0.982265 and FPR 0.0177. The findings of this research provide significant insights into the prevailing public opinion trends in the Arab world, revealing the potential of sentiment analysis as a powerful tool for policymakers, businesses, and researchers to gauge public sentiment and make informed decisions. The thesis concludes with a discussion of the limitations of the study and suggestions for future research directions, emphasizing the need for more sophisticated models and larger datasets to further enhance the accuracy and reliability of sentiment analysis in the Arabic language.