Industrial Management

Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/2406

Browse

Filters

20244

Settings

Author: search.filters.author.Fernando, IshenkaStart date: 2013

Search Results

Now showing 1 - 4 of 4
  • No Thumbnail Available
    Item
    Impact of IoT Integration on Enterprise Resource Planning (ERP) Systems: A Comprehensive Literature Analysis
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Wijesinghe, Shalani; Nanayakkara, Imasha; Pathirana, Rashmi; Wickramarachchi, Ruwan; Fernando, Ishenka
    The integration of Internet of Things (IoT) technology with Enterprise Resource Planning (ERP) systems has gained significant attention in recent years. This research study aims to provide a comprehensive analysis of the impact of IoT integration on ERP systems. The study explores the benefits, challenges, and potential solutions associated with combining IoT and ERP. The findings highlight that IoT integration with ERP offers several advantages, such as real-time data collection, improved supply chain visibility, enhanced asset tracking, and predictive maintenance capabilities. These benefits lead to increased operational efficiency, reduced costs, and better decision-making. The integration of IoT with ERP also presents challenges that need to be addressed. These challenges include data security and privacy concerns, IoT traffic, and data management. The research identifies potential solutions and best practices to overcome these challenges. Furthermore, the study discusses the implications of IoT integration on various functional areas of ERP systems, such as healthcare, manufacturing, logistics, inventory management, and customer relationship management. The research methodology includes an extensive review of existing literature and case studies. This research provides valuable insights into the impact of IoT integration on ERP systems, offering guidance for organizations considering already implemented IoT-enabled ERP solutions or currently implementing ERP solutions.
  • No Thumbnail Available
    Item
    Impact of AI-based predictive analytics on demand forecasting in ERP systems: A Systematic Literature Review
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Fathima, Fazaal; Inparaj, Rishani; Thuvarakan, Dushyanthan; Wickramarachchi, Ruwan; Fernando, Ishenka
    Artificial intelligence (AI) has revolutionized demand forecasting within Enterprise Resource Planning (ERP) systems, offering a powerful tool to enhance accuracy and efficiency in predicting future demand patterns. This literature review explores the impact of AI-based predictive analytics on demand forecasting in ERP systems by synthesizing and analyzing existing research. This paper provides a comprehensive examination of the transformative effects of AI-driven demand forecasting across diverse industries, including fashion retail, biopharmaceuticals, energy management, and transportation. We highlight the unique benefits and applications of AI-driven demand forecasting, such as anticipating customer needs, optimizing inventory levels, and making data-driven decisions, ultimately leading to a competitive edge in the marketplace. Our study emphasizes the importance of AI integration into ERP systems for businesses seeking to enhance decision-making and achieve organizational success in today's dynamic and competitive business landscape. By providing valuable insights and showcasing significant improvements in forecasting accuracy, real-time insights, supply chain efficiency, and risk management facilitated by AI-based predictive analytics, this research contributes to advancing knowledge in the field and offers practical guidance for businesses and researchers alike.
  • No Thumbnail Available
    Item
    Factors Influencing the Adoption of Agile Project Management Methodologies by Engineering Teams in the Telecommunications Industry
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Dilhara, Thamindu; Jayasinghe, Shan; Fernando, Ishenka
    This study explores the dynamic landscape of Sri Lanka’s telecommunications industry, specifically examining the correlation between engineering teams and the adoption of agile project management methodologies. With the industry’s shift towards virtual content, cloud computing, and software-driven systems, it is essential to examine the factors that impact the adoption of agile practices. Through a comprehensive literature analysis, this study identifies and analyzes ten key factors that significantly influence the integration of agile methodologies within engineering teams. Afterwards by obtaining the expert opinions, research conducts a comprehensive data analysis by identifying four key factors: organizational culture, adaptability, communication, problem-solving, and employee engagement. The study surveyed 145 telecommunication engineering teams, incorporating vital demographic characteristics to enhance the validity of its findings. Key insights reveal the critical role of organizational culture in driving agile implementation, with effective problem-solving practices contributing positively. Surprisingly, superior communication exhibits limited direct impact. Interestingly, the moderation effect of employee engagement on the relationship between organizational culture and agile adoption is negative. In contrast, employee engagement significantly influences the relationship between effective problem-solving practices and agile adoption. The study concludes with practical recommendations for creating an agile-friendly environment, investing in adaptabilitytraining, enhancing communication tools, and cultivating effective problem-solving practices. These insights aim to guide the telecommunications industry in Sri Lanka towards agile practices, fostering increased productivity, improved quality, and accelerated time-to-market.
  • No Thumbnail Available
    Item
    Antecedents Of Driving Customer Purchase Intention Via AI Based Customer Engagement Strategies In The Post Pandemic Era
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Hensman, Sheramy; Jayasinghe, Shan; Fernando, Ishenka
    This study explores the antecedents that affect customer purchase intention in the post-pandemic era, specifically through AI (Artificial Intelligence) based customer engagement strategies. By analyzing a sample size of at least 147 social media users in Sri Lanka and examining demographic profiles such as age, gender, occupation, and average monthly income, this research addresses a gap in the literature by investigating the positive impact of AI on conversion rate optimization. The study focuses on the factors of brand credibility, customer satisfaction, price sensitivity, brand attitude, and social influence, and their impact on consumer purchase intention in the context of AI-based customer engagement. This research rejects some hypotheses related to brand credibility, price sensitivity, and social influence, and accepts others related to customer satisfaction and brand attitude. It highlights the importance of customer satisfaction and brand attitude in driving consumer purchase intention in the context of AI-based customer engagement. The findings provide valuable insights for businesses and marketers seeking to optimize AI strategies for improved customer engagement and higher conversion rates.