Industrial Business Research Articles

Supply Chain Performance Evaluation for Songket Pandai Sikek SMEs: A Case Study of Rumah Songket Lima Saudara

The clothing and leather, food and chemical industries are small and medium enterprise (SME) sectors that play an important role in the economy of Tanah Datar Regency, West Sumatra. X Koto District dominates 71.2% of the clothing and leather industry business units, especially in Nagari Pandai Sikek which is famous for the production of Songket Pandai Sikek. As time goes by, the use of songket is no longer limited to traditional events, but also as a wider fashion product. Although the Songket Pandai Sikek industry continues to grow, challenges are still faced, such as high worker turnover and lack of utilization of marketing technology. The supply chain performance scores in Rumah Songket Lima Saudara in 2023 and 2024 respectively were 94.55 and 94.06 which fit in Excellent category, but the business had weaknesses in excess inventory and production volume. Strategies that can be implemented to strengthen the weaknesses include recruiting social media strategist employees, giving forecasting training for financial manager, improving customer relationship, implementing reward system for workers, creating detailed financial records and collaborating with similar businesses.

Human Capital and the Upward Occupational Mobility of Rural Migrant Workers in China

Research on the human capital and occupational mobility of Chinese rural migrant workers often focuses on how formal education is linked to upward mobility, and rarely accounts for the heterogeneity in the origin occupations. Conditioning on origin occupations, this study uses multivariable logistic regression models to explore the relationship between four human capital factors including formal education, professional training, professional certificates and the knowledge of foreign languages, and the likelihood of upward occupational mobility among rural migrant workers in the urban labor market in China. The findings confirmed the overall positive associations between human capital and upward occupational mobility, net of family background and demographic characteristics. Nevertheless, heterogeneous marginal effects exist for different human capital factors. Formal education is associated with the upward mobility of migrant workers whose first occupations are professional technicians. Foreign language proficiency is associated with the upward mobility for those with an origin occupation of industrial production personnel or business and service personnel. There is evidence for cohort differences, that foreign language proficiency is associated with the upward mobility of the older cohort with an occupational origin of industrial production personnel, and of the younger cohort with an occupational origin of business personnel, whereas high school degree only matters for the older cohort. This study contributes understanding to the mobility and stratification literature by: 1) distinguishing between four human capital factors including formal education, professional training, certificates, and foreign language proficiency, and revealing the heterogeneity in their relationship with upward mobility; 2) providing an innovative empirical approach to understand the relationship between human capital and occupational mobility that accounts for the origin and destination occupations of mobility; 3) contributing a life course perspective by revealing the link between origin and destination occupations, between education and employment, between the younger and older cohort, and between structural barriers (or incentives) and individual agency for human capital investment.

Optimizing the Supply Chain for Recycling Electric Vehicle NMC Batteries

The rapid growth of electric vehicle production has led to increased waste batteries that can no longer be used. This increase causes environmental and economic challenges. Lithium-ion battery waste harms the environment as it contains toxic and flammable chemicals. New raw materials need to be procured economically due to the need for more infrastructure and a circular economy. Therefore, the solution to overcome the impact of the accumulation of lithium battery waste is to recycle the battery. Recycling end-of-life batteries is necessary to mitigate material supply risks, reduce demand for new materials, and mitigate harmful environmental and health impacts. This study aims to provide a conceptual model for the supply chain network design of electric vehicles' Nickel Manganese Cobalt (NMC) battery recycling process. We developed a mathematical model to determine the allocation of multi-product recycling products from multi-suppliers and other related entities such as manufacturers and landfills over multiple periods. The analysis method utilizes techno-economic investment feasibility analysis and load distance method. The problem in the recycling process supply chain network is formulated in a Mixed Integer Linear Programming (MILP) model. The MILP optimization results show that the proposed model produces a globally optimal solution for allocating NMC batteries. The application of this study is to provide a solution to the treatment of waste batteries from electric vehicle end-users in Java Island, Indonesia. In addition, it can develop economic opportunities in the waste battery recycling business in the electric vehicle industry. It is building a contribution to a sustainable electric vehicle battery management system by reducing the dependence on demand for new materials from mining and analyzing the sustainability of the NMC electric vehicle battery recycling process.

Transitioning to S/4HANA: Future Planning for Cross Industry Business to Achieve Excellence in Supply Chain Digitization

Transitioning to S/4HANA: Future Planning for Cross Industry Business to Achieve Excellence in Supply Chain Digitization

Pengaruh Brand Identity Dan Food Quality Terhadap Loyalitas Pelanggan (Studi Pada Rumah Makan Rocket Chicken Di Kabupaten Majalengka)

In a franchise business, the franchisor provides a developed way of doing business, providing guidance, systems and ongoing assistance in exchange for payment of fees and/or periodic purchases. This includes franchise-based restaurant and eatery businesses in the culinary industry. This research aims to determine the influence of brand identity and food quality on customer loyalty at Rocket Chicken restaurants in Majalengka Regency. The research method used is a survey method with a descriptive verification approach. The data source is primary data, which was collected using a questionnaire. The research population is customers of Rocket Chicken restaurants whose exact number is not known. The research sample was taken randomly using an accidental sampling technique and consisted of 100 respondents. Data analysis techniques were carried out using multiple linear regression tests, partial tests, model feasibility tests, and classical assumption tests including normality tests, multicollinearity tests, heteroscedasticity tests and autocorrelation tests. The research results show that the model consisting of the independent variables brand identity and food quality is suitable for predicting customer loyalty. Partially, both brand identity and food quality have a positive and significant influence on customer loyalty at Rocket Chicken restaurants.

Cybersecurity and Supply Chain Integrity: Evaluating the Economic Consequences of Vulnerabilities in U.S. Infrastructure

Supply chain cybersecurity risks are a major threat to economic security and business continuity across critical sectors in the United States, including healthcare, finance, manufacturing, and technology. This paper assesses the impact of cyber threats on the supply chain and the measures that can be taken to prevent them, such as threat intelligence, employee awareness, and vendor security. Combining qualitative and quantitative techniques, the study complements economic loss data with qualitative insights into industry issues. Findings from the research show that preventive measures taken in cybersecurity can decrease losses for businesses in high-risk industries by more than 40 percent. Using such technologies as artificial intelligence and blockchain improves threat detection and increases transparency; however, it has certain limitations. The research offers some practical suggestions, such as increasing public-private collaboration, increasing access to sophisticated technology, and enhancing the organizations' compliance with the regulations. These insights enable individuals and organizations to create robust, secure, and sustainable supply chain networks for the future.

Capital Structure and Firm Performance: Evidence from Turkish Manufacturing Firms

One of a company's most crucial financial management decisions is its capital structure, which, when adopted correctly and successfully, can almost ensure its objectives are met. Capital structure affects the cost of capital and is important in enhancing a company's operational performance. The capital structure decision is a cornerstone of corporate financial management, influencing both short-term performance and long-term viability. To find the best debt-to-equity ratio for sustainable growth and shareholder value, businesses must carefully consider their industry dynamics, business climate, and financial objectives. Given the importance of this issue, this study's main goal is to look into how capital structure decisions affect the financial performance of Turkish firms in the food, textile, and fabricated metal subsectors between 2011 and 2020. In this study, short-term liability (STL) and long-term liability (LTL) are used as capital structure measures, return on Assets and return on equity are used as firm performance measures, and sales growth and company size are considered control variables. The findings of this study indicate a negative association between debt and the operating performance of these companies in all three sectors. This implies that companies in the aforementioned industries will have to forfeit some of their company's worth if they raise the amount of debt in their capital mix.

Tourists Behavior Prediction through Online Reviews by Analyzing their Sentiments using Machine Learning Approach

Sentiment Analysis is that part of research area where different people opinions or sentiments are extracted in form of textual data from various websites. In this paper sentiment analysis has been described along with machine learning techniques on tourist’s reviews to see their behavior towards various tourist places, hotels and other services provided by tourism industry. Emotions in the form of tourist’s reviews extracted are interpreted and classified by preprocessing of data and further feature extraction is done through machine learning highly efficient technique called deep learning. In this paper, the proposed idea has been given to use deep learning methods like CNN, RNN and LSTM rather than using machine learning classical algorithms like SVM, Naive Bayes, KNN, RF etc. Also, comparison of various machine learning and deep learning techniques working on tourist sentiments has been done here in this paper to show that deep learning techniques analyze and classify emotions and polarity with deep layers efficiently where on the other hand classical algorithms of machine learning give results not better than deep learning techniques. In this way sentiment analysis has been done and the proposed idea of this research paper is change in the machine learning techniques or methods from classical algorithms to neural network deep learning methods which in future definitely will give better results to analyze deeply the sentiments of tourists to find out the liking and disliking of various tourist places, hotels and related tourism services that will help tourism business industry to work on the gap in existing services provided by them and system can become more efficient in future. Such improved tourism system will give benefits to tourists or users in terms of better services and undoubtedly it will help tourism industry to enhance business in future. Keywords—sentiment analysis, machine learning, deep learning, tourist reviews.

Contribution of the industrial world business program to work skills and work readiness with disabilities

Contribution of the industrial world business program to work skills and work readiness with disabilities

Innovation in Alternative Material for Craft Business Industry

Rattan is one of the primary forest products in Indonesia, following timber in terms of recognition and utilization. Its unique characteristics, such as flexibility, strength, and durability, make it a preferred raw material for the furniture and handicraft industries. Despite its potential, the development of Indonesia’s rattan industry has been relatively slow. In response, the Indonesian government issued a regulation in 2011 to restrict the export of raw and semi-finished rattan to boost domestic production and value-added processes. According to the Indonesian Rattan Foundation (2010), the annual demand for semi-finished Manau rattan in Indonesia reached 619,538 tons, while the need for finished rattan stood at 533,658 tons. This demand is expected to increase due to government procurement programs supporting domestic production. Indonesia dominates the global rattan market, accounting for approximately 80% of global rattan supply, with production centers located in Kalimantan, Sumatra, Sulawesi, and Papua. West Sumatra is a notable producer, ranking as the sixth-largest rattan-producing province in the country. In Padang, West Sumatra, the rattan processing industry operates as a small and medium enterprise (SME) sector under the city’s Department of Industry, Trade, Mining, and Energy. However, the current production capacity of 48 tons per year in Padang remains insufficient to meet national demand, indicating a significant opportunity for industry expansion and value chain enhancement to strengthen Indonesia’s position as the leading rattan producer globally.

Increasing Small Businesses in the Home Chips Industry by Boosting Quality and Market Reach

Small home industry businesses (UKMRT) play a crucial role in the economy by providing income for marginalized families with limited capital. In Kedungkandang, Malang City, UKMRT, especially cassava chip producers, face challenges such as limited equipment, a lack of hygienic production knowledge, and poor financial management. This study employed Participatory Action Research (PAR) to address these issues by engaging the community in problem identification and solution implementation. Training sessions focused on financial management, hygienic production techniques, and marketing strategies. Introducing modern cassava-cutting tools and improved packaging significantly enhanced production efficiency and product appeal. Results indicated increased production capacity, higher product quality, and improved financial practices among partners. The economic impact was evident as daily income for producers increased substantially, and marketing expanded beyond local markets from 200 thousand rupiahs per day to 500 thousand rupiahs. This holistic approach, integrating economic, social, and technological aspects, highlights the potential for significant socio-economic transformation in similar communities. Further geographical expansion and product diversification are recommended to sustain and enhance these positive outcomes. The study demonstrates a replicable model for community service that effectively addresses the multifaceted needs of small home industry businesses.

Strategi Pemasaran Digital untuk Meningkatkan Loyalitas Pelanggan di Era Media Sosial

This study examines digital marketing strategies implemented by businesses in the creative industry and their relationship with customer loyalty. The crucial issue raised was how businesses can leverage social media to increase customer engagement and loyalty in the midst of fierce competition. The problem faced is a lack of understanding of the effectiveness of digital marketing strategies in building long-term relationships with customers. The purpose of this study is to explore and analyze the strategies used and their impact on customer loyalty. The research method used is observation and interviews with business people who are active on social media. The results of the study show that consistent interactions and relevant content contribute significantly to customer loyalty. The conclusion of this study emphasizes the importance of implementing the right digital marketing strategy to support business sustainability in a sustainable e-commerce ecosystem

Studying strategic behaviour of small industrial enterprises in the context of the organizational and industry life cycle concepts

Unlike large corporations whose business patterns have been extensively studied and categorized, there is a lack of research on small business strategies, leaving them largely unexplored. The article explores the strategic behaviour of small industrial enterprises in Russia within the organizational and industry life cycle concept. The research methodology is based on strategic management theory and the concept of the life cycle. The research methods include panel data analysis, the Beta coef f icient calculation, and the matrix method. The information base is the reporting data of 134 small enterprises from industries at different stages of the life cycle: metal casting (growth) and newspaper printing (maturity). Statistics for analysis were obtained from the SPARK Interfax database for the period of 1999–2021. We identified three types of strategic behaviour (‘aggressive’, ‘de fender’, and ‘counterstrategy’) and assessed their prevalence among small enterprises in the two industries under consideration. The results showed that mature small enterprises with an ‘aggressive’ intuitively strategic behaviour are the predominant type of business in a mature industry, while for small enterprises in a growing industry ‘defender’ and ‘counterstrategy’ are the prevalent strategies at all the life cycle stages. This paradox additionally proves the validity of our idea of the intuitively strategic behaviour of small businesses. Our findings contribute to the development of the SME life cycle theory and strategic management, can be used to adjust industry policy and government support measures, and can also be of interest to managers of small enterprises.

Information Needs Analysis For Inventory Management System Development Based On Existing Conditions In MSMEs

The purpose of this research is to strengthen its competitive advantage in the digital business industry in Indonesia by utilizing digital solutions to fulfill consumer needs, considering increasing market rivalry and the progress of digital products. The interview was conducted with micro, small, and medium-sized enterprises (MSMEs) located in West Java from January to June 2024 to identify the issues and needs of MSMEs. The identified problems need to be further processed using the System Development Life Cycle method. The results are expected to be utilized in the development of an Inventory Management Information System that can support the effectiveness of inventory management by MSMEs.

Inclusion of Women in the Mining Sector: Challenges and Opportunities Through Education

Labor dynamics have changed in recent years, and women have increased their participation in various activities within the production and business industries. One of these sectors is mining, which presents both challenges and opportunities to promote gender equality and decent work. In light of this, the objective of the present study is to identify the limitations faced by women in the mining sector, framed within personal, family, social, and labor aspects, in relation to their educational level. Due to the nature of the study, a cross-sectional, descriptive, and non-experimental investigation was proposed. The sample consisted of more than 50 companies distributed throughout the Mexican Republic, with a total of 316 female workers in the mining sector. The main results show greater limitations in labor and family aspects. Moreover, educational levels directly affect how women perceive the impact of working in mining on the various areas in which they operate.

Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost.

As the business world shifts to the web and tremendous amounts of data become available on multilingual mobile applications, new business and research challenges and opportunities have been explored. This research aims to intensify the usage of data analytics, machine learning, and sentiment analysis of textual data to classify customers' reviews, feedback, and ratings of businesses in Jordan's food and restaurant industry. The main methods used in this research were sentiment polarity (to address the challenges posed by businesses to automatically apply text analysis) and bio-metric techniques (to systematically identify users' emotional states, so reviews can be thoroughly understood). The research was extended to deal with reviews in Arabic, dialectic Arabic, and English, with the main focus on the Arabic language, as the application examined (Talabat) is based in Jordan. Arabic and English reviews were collected from the application, and a new model was proposed to sentimentally analyze reviews. The proposed model has four main stages: data collection, data preparation, model building, and model evaluation. The main purpose of this research is to study the problem expressed above using a model of ordinal regression to overcome issues related to misclassification. Additionally, an automatic multi-language prediction approach for online restaurant reviews was proposed by combining the eXtreme gradient boosting (XGBoost) and particle swarm optimization (PSO) techniques for the ordinal regression of these reviews. The proposed PSO-XGB algorithm showed superior results when compared to support vector machine (SVM) and other optimization methods in terms of root mean square error (RMSE) for the English and Arabic datasets. Specifically, for the Arabic dataset, PSO-XGB achieved an RMSE value of 0.7722, whereas PSO-SVM achieved an RSME value of 0.9988.

Data Acquisition and Management in Industrial Businesses Fundamentals and Methodologies

In industrial enterprises, data acquisition is an essential procedure, basically in the industry 4.0 context. It entails taking signals and converting them into digital values that a computer can manipulate. In order to transform analog waveforms into modern values for further processing, information gathering systems are essential. This article focuses on the process of acquiring data in industrial enterprises throughout the age of Industry 4.0 reviewing the constituents of data gathering systems and the significance of accurate and dependable data in portraying industrial processes. In addition, the study examines the classification of production systems according to criteria that influence data accessibility, as well as the various techniques and approaches used for data acquisition. The limitations of human data collection are highlighted, along with the benefits of automated and semi-automated data capturing technologies. Management support systems may get data from industrial automation systems, which are also investigated in the research. Using dedicated servers and communications protocols to consolidate data, it investigates the issues with industry-wide fragmentation in automation systems. The research goes deeper into how machine vision, barcodes, and RFID devices are used to gather data. Finally, the paper emphasizes the need of analyzing the company's organizational and technical environment and proposes a strategy for building a Manufacturing Information Acquisition System (MIAS).

Chinese language education policies in the Arabian Gulf: new players, discourses and linguistic markets

ABSTRACT This Special Issue (SI) aims to frame and examine the rising interest in Chinese language education policies in the six oil-rich Arabian Gulf Cooperation Council (GCC) countries, which consist of Saudi Arabia, Qatar, Bahrain, Oman, Kuwait, and the United Arab Emirates (UAE). Grounded in a Critical Cultural Political Economy of Education (CCPEE) approach [Robertson, S. L., and R. Dale. 2015. “Towards a ‘Critical Cultural Political Economy’ Account of the Globalising of Education.” Globalisation, Societies and Education 13 (1): 149–170. https://doi.org/10.1080/14767724.2014.967502], it investigates how the growing number of degree programmes and courses in the Chinese language as well as activities promoting Chinese culture, with generous logistic, financial, and administrative support from the GCC governments, are played out within particular ‘education ensembles’. It also explores the types of socio-material practices and discourses that are deployed by different players—governments, universities, schools, business industries, teachers, learners, researchers, and investors—to index the value of Chinese and Chinese language education

Runtime defect prediction of industrial business processes: A focused look at real-life SAP systems

Runtime defect prediction of industrial business processes: A focused look at real-life SAP systems

Suntsova O. Circular economy impact on global sustainable growth in international industrial business. Financial and Сredit Systems: Prospects for Development. №4(15) 2024. P. 140-152. DOI: https://doi.org/10.26565/2786-4995-2024-4-11

Suntsova O. Circular economy impact on global sustainable growth in international industrial business. Financial and Сredit Systems: Prospects for Development. №4(15) 2024. P. 140-152. DOI: https://doi.org/10.26565/2786-4995-2024-4-11