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International Journal of Business and Management Technology in Society (IJBMTS)
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : -     EISSN : 30254256     DOI : -
Core Subject : Economy, Social,
Economics, Econometrics & Finance Social Sciences
The International Journal of Business and Management Technology in Society (IJBMTS) is a peer-reviewed, open-access journal that publishes original research articles, review articles, and case studies in the fields of business, management, and management of technology. The journal aims to provide a platform for scholars, practitioners, and policymakers to exchange ideas and share knowledge on how business and management of technology practices can contribute to the advancement of the society. The journal welcomes submissions from authors around the world and encourages interdisciplinary perspectives. Focus and Scope -Human Resource Management -Operations & Supply Chain Management -Accounting & Governance -Financial Management -International Business -Information Management -Management of Technology -Enterprise System -Innovation & Entrepreneurship -Social Entrepreneurship -Knowledge Management -Business Model & Development -Economics & Econometric -Strategic Management -Small Medium Enterprises -Marketing & Branding -Corporate social responsibility
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 2 No. 2: December 2024" : 5 Documents clear
Artificial Intelligence (AI) Technology Trends in Human Resource Productivity: A Bibliometric and Content Analysis Zahril Maulana Jilham Al'ula; Astra Savero Qomara; Tyassatrio Kuncorowibowo; Syarifa Hanoum
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.1023

Abstract

Purpose – This research aims to show research trends in the field of AI implementation in the human resources realm and its relationship with human resource productivity Methodology – This research combines bibliometric analysis with content analysis methods. Bibliometric analysis is carried out by quantitative and statistical analysis of a set of data that is linked using bibliometric indicators that represent a set of topics that are the research area in this study. Then the findings from the bibliometric method are supported by content analysis from various studies in this research area, so that it can produce output with a clearer perspective. Findings – This research show that Artificial Intelligence (AI) can have significant effect on productivity in some case, but it must also be acknowledged that companies must also be wise in ensuring that the work to be adapted with the help of AI is appropriate, because the implementation of AI has not yet reached the point where all human work can be assisted or replaced by AI. Research Limitation – This research was conducted only through the findings on several previous research, articles, and the data obtained from Scopus only. Practical Implications – Based on the bibliometric analysis of recent trends in AI technology and its impact on human resource productivity, it is recommended that organizations invest in AI-based HR tools and systems to improve their productivity and efficiency. The study highlights the need for HR professionals to stay up to date with the latest AI trends and technologies to remain competitive in the job market.
Optimizing Product Delivery through Two-Dimensional Time Warping Demand Allocation under Uncertainty Meilanitasari, Prita; Vanany, Iwan; Ma'ady, Mochamad Nizar Palefi; Isrofi, Nisa
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.1341

Abstract

Purpose – This study aims to optimize delivery operations by implementing a flexible clustering method to handle demand uncertainty and improve logistics efficiency. Methodology – This study develops a clustering algorithm using a two-dimensional time-warping approach to group demand points based on spatial proximity and demand characteristics. The methodology consists of three stages: 1) processing data on point distances, 2) clustering using two-dimensional time warping, and 3) validating through silhouette analysis. Findings – This study resulted in optimal and efficient demand clustering through location clustering with a Silhouette coefficient value of 0.7 or an accuracy and feasibility level of 70%. The algorithm also shows improved computational efficiency compared to traditional approaches, making it suitable for practical applications in uncertain and dynamic environments. Practical implications – This study holds significant importance for businesses in the logistics and retail sectors. Through demand clustering, businesses can effectively group customer demands and utilize this information to optimize inventory management and delivery solutions.
Feasibility Study of Bitumen Asphalt (Asbuton) Plant in Mass-Production Scale Silalahi, Rochelle Trixie; Hakim, Muhammad Saiful; Baihaqi, Imam; Sinansari, Puti; Putri, Anandita Ade
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.7930

Abstract

Purpose – This study aims to assess the operational and financial feasibility of mass-producing Asbuton (Buton natural asphalt) as a sustainable alternative material for road construction in Indonesia. Methodology – This study adopts a feasibility study framework integrating operational and financial analyses. The operational assessment covers plant location selection, plant capacity determination, facility layout planning, and production process evaluation. Financial feasibility is analyzed through projected cash flow estimation based on capital and operational expenditures, employing investment appraisal indicators such as Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP). A sensitivity analysis is further conducted to evaluate the impact of price variations on project viability. Findings – The results indicate that the proposed Asbuton production plant is both operationally and financially feasible. The financial indicators demonstrate satisfactory investment performance, while sensitivity analysis shows that the project remains viable under reasonable fluctuations in key economic variables. Technological advancement and efficient operational planning play a critical role in improving cost efficiency and competitiveness. Originality – This study offers a comprehensive feasibility assessment by integrating operational design, financial evaluation, and sensitivity analysis for large-scale Asbuton production. It contributes empirical evidence to the limited literature on natural asphalt commercialization in emerging economies, particularly Indonesia.
Evaluating the Efficiency and Productivity Effects of Cross-Border Acquisitions Using Data Envelopment Analysis (DEA) Hanoum, Syarifa; Sa'adah, Silviana Khalilatus; Ratih, Irene Kanina; Rofifah, Jihan; Nikmah, Uliyatun; Shubbak, Mahmood
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.8784

Abstract

Purpose – This research examines the impact of cross-border acquisitions on the efficiency and productivity of acquired companies, with a specific focus on MSA, an automotive firm. Methodology – We employ Data Envelopment Analysis (DEA) to assess total factor productivity and compare MSA’s performance before and after its acquisition by Michelin. Findings – MSA’s efficiency fluctuated over time, peaking in Q1 2021 with a score of 1 but declining in Q1 2022, indicating room for improvement. The Mann-Whitney test results show no significant change in MSA’s efficiency following the acquisition, suggesting the merger did not notably enhance performance. Practical implications – Managers should concentrate on optimizing material, labor, and capital management, while maintaining continuous operational monitoring. A proactive approach to the implications of strategic decisions, such as cross-border acquisitions, is essential for sustained high performance and long-term success.
Barriers to Digital Transformation Implementation in Operations and Supply Chain Management: A Systematic Literature Review (SLR) Inayah, Nur Azmi; Baihaqi, Imam
International Journal of Business and Management Technology in Society Vol. 2 No. 2: December 2024
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30254256.v2i2.8889

Abstract

Purpose – This study seeks to identify and summarize the principal barriers to the implementation of digital transformation in operations and supply chains. Methodology – This research utilizes a Systematic Literature Review (SLR) methodology in accordance with PRISMA criteria. A thorough literature search was performed utilizing the Google Scholar database, concentrating on peer-reviewed articles released from 2019 to 2024. Studies were evaluated according to established inclusion and exclusion criteria. From the initial collection of discovered papers, 20 studies were chosen and examined to systematically discern reoccurring themes and categories of obstacles to digital transformation. Findings – The analysis indicates that digital transformation in operations and supply chain management is obstructed by several significant barriers, including inadequate digital capabilities, resistance to organizational change, interoperability challenges, insufficient infrastructure readiness, and cybersecurity issues. These obstacles diminish operational efficiency, disrupt process integration, and undermine supply chain resilience, thereby restricting the potential advantages of digital transformation programs. Originality – This study enhances the literature by offering a systematic synthesis of challenges to digital transformation in operations and supply chain environments. The study consolidates fragmented information, emphasizing notable research gaps about the varying effects of different barriers on the efficacy of digital transformation. The findings provide significant insights for scholars and practitioners, indicating pathways for future study aimed at creating comprehensive frameworks for evaluating and alleviating impediments to digital transformation.  

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