Technology Management Strategies Research Articles

Towards Good Governance in the Management of Educational Institutions in Cameroon: Importance, Challenges and Opportunities

Purpose: This conceptual paper explored the path toward institutionalisation of good governance in the management of educational institutions in Cameroon. Aim was to identify key principles, assess challenges to effective governance, and explore opportunities for improvement, with the view to offer actionable recommendations that could help enhance educational management in Cameroon. Materials and Methods: A qualitative approach that combines personal observations with a comprehensive textual review was employed. The review examined national and international policy documents, strategic plans, reports and academic articles to clarify theoretical constructs and practical applications of good governance in education. Recommendations were based on personal reflections and literature analysis. Findings: The education sector has evolved from being simpler and less competitive to a complex, competitive and more demanding landscape, requiring technology and advanced management strategies centered on governance principles like transparency and accountability. In Cameroon, historical, socio-economic, political, and structural challenges hinder the establishment of good governance in education. However, there is room for educational managers to navigate these realities and promote effective governance, which is essential for unlocking education’s transformative potential and achieving socioeconomic development goals. Implications to Theory, Practice and Policy: The various ministries of education should work in synergy with the other stakeholders to implement a comprehensive training programme for educational managers; invest more resources in educational technology for better administrative efficiency; strengthen monitoring and auditing of expenditures; and enhance the capacity of decentralised management structures to effectively address local needs. These strategies should help create a more accountable and responsive education management framework for Cameroon.

Impact of Plai-Zampen programs on librarians' professional development for technological advancement and management

The purose of this study is to assess the impact of the programs initiated by the Philippine Librarians Association, Inc.- Zamboanga Peninsula (PLAI-ZamPen) for the last 5 years on Librarians’ Professional Development for Technological Advancement and Management. It highlights librarians' adaptation to technological demands, emphasizing skills in software, systems, and data analysis. Employing a quantitative research design with a descriptive survey method, the study utilizes 86 librarian respondents to evaluate its profiles, program impact, and effectiveness variations based on library types, membership duration, and roles. Using tools like the Kruskal-Wallis H Test and Weighted Mean, the study provides a comprehensive analysis, emphasizing the importance of ongoing professional development for libraries to remain relevant and responsive in hybrid learning environments. The findings revealed a significant positive impact, with programs effectively equipping librarians with essential skills and fostering a culture of innovation. The analysis of membership demographics highlights a predominance of academic librarians and a mix of experienced and novice members, underscoring the inclusivity and effectiveness of PLAI-ZamPen's initiatives. In conclusion, this study this affirm that the programs initiated by PLAI-ZamPen significantly enhance librarians' professional development, particularly in the realms of technological advancement and management. The positive impact of the programs extend beyond individual skill enhancement; it also bolsters libraries' abilities to adapt to evolving community needs, thereby ensuring continued relevance and excellence in service delivery. It is recommended that continued innovation and expansion of professional development programs, focusing on emerging technological trends and management strategies will be taken into account. Thus, it will enhance librarians' proficiency in digital tools and foster global collaboration, ensuring that libraries remain essential hubs of knowledge and service excellence.

Assessing the Impact of Digitalization on MSMEs Performance

This study aims to examine the impact of digitalization on Msmes performance, as well as challenges and opportunities in digitalization and effective technology management strategies. The digital era presents MSMEs with a number of obstacles, including scarce human and financial resources, poor digital infrastructure, and little technical knowledge and awareness. However, MSMEs can also benefit significantly from digital transformation, which opens up new markets to them, increases operational efficiency, and gives them the capacity to use data analysis to make better decisions. This research discovers that good technology management techniques are essential for the digital transformation of MSMEs through a qualitative approach and literature review. The strategies include of creating a strategy for technology plan that is compatible with business goals, choosing and integrating the right systems, and skill-building programs for employees. The purpose of this study is to investigate and determine the most innovative strategies for MSME digital business development. The study concludes that MSMEs can increase productivity and innovation, automate business operations, and save operating expenses by implementing digital technology properly.

Implications of artificial intelligence

The artificial intelligence (AI) revolution is underway. AI has become omnipresent in medicine, and its broad capabilities have permitted significant developments in many subspecialties including spine surgery. With AI, spine surgeons have been able to perform advanced computational analytics on vast amounts of data, allowing for solutions in each step of patient care from preoperative evaluation and planning, intraoperative execution, and postoperative evaluation. The tremendous potential of AI in medicine is clear and exciting. However, as the utility of AI in clinical practice expands, the medicolegal implications of this technology are poorly understood. In this chapter, we explore the existing technology, ethical considerations, legal challenges, and risk management strategies as it relates to AI in the field of spine surgery.

Penerapan Supply Chain Management di PT Nippon Indosari Corpindo Tbk

This research discusses the application of Supply Chain Management (SCM) at PT Nippon Indosari Corpindo Tbk., one of the leading companies in the bakery industry in Indonesia. Focusing on enhancing operational efficiency and reducing production costs, this study explores how PT Nippon Indosari Corpindo Tbk. integrates advanced technology and Supply Chain Management strategies to maintain product quality while minimizing losses. Through the use of the Just In Time (JIT) concept, Advanced Planning & Optimization (APO) tool, and Radio Frequency Identification (RFID), the company has successfully improved inventory management, expedited distribution, and maximized customer satisfaction. The research findings show that effective SCM implementation has reduced the bullwhip effect, increased transparency in the flow of raw materials and finished products, and supported the sustainability of the company's operations. Thus, this study provides important insights into the benefits of SCM in the food and beverage industry, especially for companies operating on a large scale with dynamic market demands

Examining the impact of green technological specialization and the integration of AI technologies on green innovation performance: evidence from China.

China's commitment to achieving carbon neutrality by 2060 has sparked scholars' interest in examining the environmental ramifications of green technologies in the digital era. While plenty of them provide eco-efficiency policy such as increasing R&D investment or stimulating green exports, little attention has been paid to the firm-level technological management and recombination strategies such as differentiation/specialization of green portfolios along with AI integration, which can significantly impact the pace of net-zero transitions. To address these gaps, this study investigates the moderating effect of technological specialization on levels of AI integration into green technologies estimated by green-AI technological distance and enterprises' innovation performance in Chinese contemporary contexts. Regression results of fixed-effect model in Chinese patent data (2011-2020) indicate that enterprises' green innovation performance is significantly improved as AI integrates more into the green technologies due to the legitimacy and the inability to appropriate more green values. Interestingly, specialized green-technological enterprises demonstrate superior performance in integrating distant AI technologies. This occurrence could potentially be driven by the governments' incentives and the organization's risk attitudes, shaping green innovation outcomes. Hence, the study underscores the importance of considering both the AI integration and green specialization in shaping innovation outcomes amidst green transitions.

Supply Chain Resilience: Adapting To Global Disruptions and Uncertainty

In an increasingly interconnected world, supply chain resilience has emerged as a critical factor for businesses to navigate disruptions and uncertainty. This paper delves into the dynamic landscape of supply chain management, emphasizing the need for organizations to adapt and fortify their operations against a myriad of challenges, ranging from natural disasters to geopolitical tensions and pandemics. Drawing on a comprehensive review of existing literature and real-world case studies, this research explores the key components of supply chain resilience and identifies best practices for building robust systems. It examines the role of technology, collaboration, and risk management strategies in enhancing resilience across various industry sectors. Furthermore, this paper sheds light on the impact of recent global disruptions, such as the COVID-19 pandemic, on supply chains worldwide, highlighting both the vulnerabilities exposed and innovative responses adopted by organizations. A nuanced analysis elucidates the lessons learned and opportunities for improvement in supply chain resilience frameworks. By synthesizing insights from academia and industry, this study offers practical recommendations for executives and policymakers to bolster supply chain resilience in an era characterized by volatility and complexity. It underscores the imperative for proactive measures, agile strategies, and continuous monitoring to mitigate risks and ensure operational continuity in the face of uncertainty. Ultimately, this research contributes to a deeper understanding of supply chain resilience as a strategic imperative, empowering organizations to thrive amidst global disruptions and safeguard the flow of goods and services in an interconnected global economy.

Utilization of Data Analytics to Enhance Operational Efficiency in Manufacturing Companies

In the digital era, manufacturing industries confront challenges like heightened global competition and intricate production processes, urging them to boost efficiency and productivity. Amidst these circumstances, Big Data emerges as a pivotal opportunity to enhance manufacturing performance. Big Data, characterized by vast volumes of data, utilizes advanced data mining to machine learning techniques for analysis. Data analytics, an interdisciplinary field, profoundly impacts manufacturing operations, enabling deeper insights into production processes. By analyzing production data, companies identify inefficiencies, streamline workflows, and enhance operational efficiency and productivity. Predictive maintenance through sensor data analysis prevents machine failures, while logistics data analysis optimizes supply chains and inventory management, reducing costs and enhancing competitiveness. However, implementing Big Data analytics presents challenges such as rapid data growth, diverse data sources, real-time insights, skill shortages, and data fragmentation. Overcoming these hurdles requires robust technology, skilled personnel, and effective data management strategies. Examples of Big Data analytics applications include customer behavior analysis by Amazon and Netflix, fraud detection in insurance, and urban mobility optimization. Success factors in data analytics implementation include effective data-driven communication, technology integration, and skill enhancement. In conclusion, implementing Big Data Analytics in manufacturing promises significant benefits in operational efficiency, product quality, and competitiveness. Overcoming challenges necessitates robust strategies and consideration of ethical and security issues, ensuring responsible data usage. With a deep understanding of Big Data Analytics, manufacturing companies can leverage this technology to achieve higher efficiency and competitiveness in the global market.

Crop Classification Combining Object-Oriented Method and Random Forest Model Using Unmanned Aerial Vehicle (UAV) Multispectral Image

The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing, offer a novel solution for precise crop identification. In this study, we evaluated a methodology that integrates object-oriented method and random forest (RF) algorithm for crop identification using multispectral UAV images. The process involved a multiscale segmentation algorithm, utilizing the optimal segmentation scale determined by Estimation of Scale Parameter 2 (ESP2). Eight classification schemes (S1–S8) were then developed by incorporating index (INDE), textural (GLCM), and geometric (GEOM) features based on the spectrum (SPEC) features of segmented objects. The best-trained RF model was established through three steps: feature selection, parameter tuning, and model training. Subsequently, we determined the feature importance for different classification schemes and generated a prediction map of vegetation for the entire study area based on the best-trained RF model. Our results revealed that S5 (SPEC + GLCM + INDE) outperformed others, achieving an impressive overall accuracy (OA) and kappa coefficient of 92.76% and 0.92, respectively, whereas S4 (SPEC + GEOM) exhibited the lowest performance. Notably, geometric features negatively impacted classification accuracy, while the other three feature types positively contributed. The accuracy of ginger, luffa, and sweet potato was consistently lower across most schemes, likely due to their unique colors and shapes, posing challenges for effective discrimination based solely on spectrum, index, and texture features. Furthermore, our findings highlighted that the most crucial feature was the INDE feature, followed by SPEC and GLCM, with GEOM being the least significant. For the optimal scheme (S5), the top 20 most important features comprised 10 SPEC, 7 INDE, and 3 GLCM features. In summary, our proposed method, combining object-oriented and RF algorithms based on multispectral UAV images, demonstrated high classification accuracy for crops. This research provides valuable insights for the accurate identification of various crops, serving as a reference for future advancements in agricultural technology and crop management strategies.

Prospects and Management Strategies for High Noise, Soft Geological and Strong Earthquake Environments

With global warming, environmental degradation is becoming increasingly severe, and the impact on power transmission and transformation equipment is increasing. The changing environment will also have cross impacts, and people are paying more attention to environmental protection. Therefore, under complex environmental conditions, research on new technologies continues, and the emergence of new technologies can improve efficiency and reduce costs. This article focuses on three typical environments: noise environment, soft geological environment, and seismic environment, with a focus on analysing their latest technological situation and management strategies. At the same time, it proposes future development directions, guides the emergence of new business models and service methods, and promotes industry innovation and change.

INNOVATIONS IN PROFESSIONAL TRAINING OF RESEARCH ADMINISTRATORS IN THE USA AND UKRAINE: A TECHNOLOGICAL APPROACH

The evolving landscape of research management and administration at the universities has seen remarkable transformations in recent years, expanding the role of research administrators to include strategic planning, project management, funding acquisition, and regulatory compliance. This transformation has been significantly influenced by innovative technologies, streamlining various aspects of their responsibilities, from data management to project planning and funding identification. Moreover, the integration of technology has enhanced their ability to contribute to strategic decision-making and adapt to evolving research environments. Innovative training methodologies have reshaped research administrators’ education, with e-learning platforms, simulation, gamification, virtual reality, augmented reality, artificial intelligence, and data analytics offering diverse and dynamic learning experiences that cater to the varied needs of research administrators or managers. A comparative analysis of research administration and management training in Ukraine and the United States reveals the global diversity in training approaches. However, challenges related to digital literacy and resource constraints are evident, underscoring the need for cross-border collaborations to address these issues and promote best practices in research administration and management. As a result of these findings, research administrators are now better equipped to excel in their multifaceted roles, thanks to technology and innovative training methods. The global landscape of research administration training presents opportunities and challenges that require ongoing attention and adaptation. Further research in this field is warranted, focusing on evaluating the effectiveness of various training methodologies, assessing the long-term impact of technology integration, exploring successful cross-border collaboration models, addressing digital literacy challenges, and investigating the adaptation to continuous technological advancements and change management strategies in this field. These future research directions aim to enhance the understanding of how research administrators can thrive in the ever-evolving research landscape.

Utilizing Information and Communication Technology in Scalable Management Strategies for Teacher Development

INTRODUCTION: Teachers are human resources who play an important and strategic role in the success of learning so they must fulfill adequate competencies. Teachers with low competence will not be able to produce students who excel both academically and non-academically. Efforts to improve teacher competency include education and training. 
 OBJECTIVE: This research aims to see how information and communication technology is used in developing teachers' pedagogical and professional competencies. 
 METHODS: This research was carried out using a descriptive qualitative approach. The data used in this research was obtained from various relevant sources. 
 RESULTS: The results of this research found that increasing teacher pedagogical and professional competence through the integration of Information and Communication Technology (ICT) and scalable management strategies opens up new perspectives on the importance of investing in the development of teaching staff. 
 CONCLUSION: The alignment of modern pedagogical approaches with the use of technology and efficient management strategies allows teachers to develop as more effective and competitive educators. Increasing pedagogical competence allows educators to create more dynamic and relevant learning environments for students. By incorporating innovative teaching methods, such as the use of digital tools and resources, teachers can adapt learning to students' diverse learning styles.

Pengembangan UMKM Pesona Plastic melalui Produk Desain dari Limbah Plastik dengan Pemanfaatan Teknologi dan Strategi Manajemen Bisnis Berkelanjutan

The development of Micro, Small, and Medium Enterprises in Pesona Plastic, Batubulan Village, Gianyar Regency, Bali, focuses on the development of design products that use plastic waste as raw material. This effort involves the utilization of technology and sustainable business management strategies. The methods used include training and mentoring. This article outlines concrete steps in the development of Pesona Plastic UMKM, including the plastic waste processing process, the development of innovative design products, and the implementation of sustainable business management strategies. Activities conducted include the procurement of equipment and various training sessions, such as product design training for accessories and fashion, website integration training, interior product design training, digital marketing training, packaging design training, entrepreneurship and financial management training for UMKM and youth, social media marketing training, layout design, and space organization training, as well as equipment usage workshops. The results are successful efforts to reduce the impact of plastic waste, create high-quality products, and improve the well-being of the Pesona Plastic UMKM community in Batubulan Village. The follow-up plan for this program involves collaboration between IDB Bali and Pesona Plastic UMKM, with future involvement of students for practical training and the realization of designed products that serve a useful purpose.

TECHNOLOGY AND INNOVATION TO GROWTH OF ENTREPRENEURSHIP AND FINANCIAL BOOST: A DECADE IN REVIEW (2013-2023)

The study, "Technology and Innovation to Growth of Entrepreneurship and Financial Boost: A Decade in Review (2013-2023)," critically explores the intersectionality of technology, innovation, and entrepreneurship, delineating their collective impact on financial growth and economic enrichment over the past decade. Through an exhaustive examination of empirical data, literature reviews, and holistic case studies, this paper presents a nuanced analysis of the transformation and evolution of the entrepreneurial landscape within the context of the burgeoning advancements in technology and innovation management strategies. The investigative journey commences with an insightful delineation of the objectives and research questions aimed at understanding the multifaceted dynamics between technological proliferation, innovative applications, and entrepreneurial growth. Subsequently, a meticulous review of literature unveils the underpinning theoretical frameworks and foundational concepts, elucidating the symbiotic relationship between technology and entrepreneurship. Concepts such as the diffusion of innovations, disruptive technologies, and stakeholder theory are explored to comprehend the profound impacts on entrepreneurial ventures and their concomitant challenges and opportunities. The study further delves into the empirical exploration of the evolution of the entrepreneurial landscape from 2013 to 2023, offering a granular perspective on the diverse technological trends, market fluctuations, and innovative breakthroughs that have characterized this period. The challenges and risks associated with technology and innovation in entrepreneurial settings are highlighted, including discussions on market competition, technological obsolescence, intellectual property conflicts, and ethical considerations, providing a balanced viewpoint on the manifold aspects of entrepreneurial progression. Diverse real-world case studies of companies such as Tesla Inc., Beyond Meat, Square Inc., and Zoom Video Communications offer tangible manifestations of the intricate interplay between technology, innovation, and entrepreneurship. These cases exemplify the varied approaches and adaptive strategies employed by enterprises to navigate challenges, leverage opportunities, and effectuate significant market transformations and societal impacts. These serves as exemplary models of resilience, adaptability, and visionary leadership in the face of uncertainties and market dynamics. In conclusion, the study synthesizes the gleaned insights to project future directions in entrepreneurship, emphasizing the imperatives of sustainability, inclusivity, and ethical conduct. The study posits that the future of entrepreneurship will be marked by enhanced emphasis on social impact, environmental considerations, and the integration of emerging technologies. The recommendations outlined in the study advocate for strengthened ecosystem support, fostering of collaboration, and promotion of responsible and ethical business practices to cultivate a conducive and equitable entrepreneurial environment. This comprehensive exploration contributes significant insights to the academic discourse on technology, innovation, and entrepreneurship, offering valuable implications for practitioners, policymakers, and academia, thereby enriching the understanding of the dynamic interdependencies between these pivotal domains.
 Keywords: Entrepreneurship, Technology, Innovation, Financial, Economic Growth, Transformation.

Change Management And Job Performance Of Office Managers In Tertiary Institutions In Rivers State

This study examined change management and Job performance in manufacturing companies in Nigeria. Relevant conceptual, theoretical and empirical literatures were reviewed. The study conceptualises change management in terms of technological change, leadership change and change management strategies. This study was anchored on organizational change and Lewin`s Three Step Model. The study was carried out in eight (8) tertiary institutions in Rivers State. Descriptive survey design was adopted in the generation of data. The instrument for data collection used in this study was the questionnaire. The population of the study consisted of eight hundred and thirty-six (836) Office and information managers in seven public tertiary institutions in Rivers State. The respondents to this research are 270 participants which constituted the sample size obtained through Taro Yamene Sample Size Determination Formula. Descriptive statistics (mean, standard deviation, and percentages) were used as statistical tools for univariate analysiis the data, while simple linear regression analysis was used as statistical tool for bivariate analysis with the Statistical Package for Social Sciences (SPSS). Change management strategies have effect on Job performance in manufacturing companies. Leadership changes have a positive influence on job performance of office managers in the tertiary institutions in Rivers State. The study concluded that change management is a determinant of office managers’ job performance in in tertiary institutions. The study recommends that technology change had influenced employee performance since it simplifies the work to be done, thereby making work more efficient. Organizations which implement new technology should provide proper training to their employees to increase their performance. Every organization should build strong organizational management strategies that help to build good relationships based on their values, norms, behaviours, and perceptions. Leadership changes leaders‟ mind-set, style, and behavior. The change process they design as a result of their orientation must encourage employees to want to participate, to choose to contribute, rather than force them to do so.

Re-investigation of the Mediating Effect of Brain Activities between Dispositional Factors and Hazard Recognition: A Multilevel Logistic Regression Approach

Understanding the relationships among dispositional factors, brain activities, and hazard recognition is important for developing auxiliary safety technologies and improving construction safety performance. However, current logistic statistical models have embedded potential biases into the interpretation of brain activities. The purpose of this study was to re-investigate the mediation effect of brain activities between dispositional factors (risk propensity, work experience, and injury history) and hazard recognition performance (HRP). An experiment was designed in which 71 construction workers each completed 120 hazard recognition trials (N = 8520), while the research team used an electroencephalogram recorder to record the brainwaves of the participants. The data were analyzed by the multilevel logistic regression method, and the results showed that the brain activities in FP1, FP2, and AF3 significantly mediated the relationship between dispositional factors and HRP. The findings theoretically supplement the understanding of brain activities in different hazard cognitive stages for hazard recognition. The results should contribute to the development of neuro-engineering technology and safety management strategies.

Research on Key Technologies and Comprehensive ManagementStrategy of New Energy Hybrid Electric Vehicles

New energy hybrid electric vehicles (HEVs) have emerged as a promising technology for reducing the usage offossil fuels and emissions in the transportation sector. This paper reviews the key technologies and comprehensivemanagement strategy of new energy HEVs. The key technologies of new energy HEVs include battery technology,power technology, and comprehensive management strategy. Battery technology must provide high energy density, longcycle life, and high power density, while power technology must provide high efficiency, low emissions, and smoothpower delivery. The comprehensive management strategy includes energy management control and a battery thermalmanagement system, which optimize the battery’s energy flow and temperature control. The paper discusses the basicprinciples and components of new energy HEVs and examines the developments and research in each technology.The article also explores the challenges and opportunities of new energy HEVs. It concludes that the developmentand adoption of new energy HEVs are essential for achieving a sustainable transportation system and reducing thetransportation sector’s environmental impact.

Research on Truck Lane Management Strategies for Platooning Speed Optimization and Control on Multi-Lane Highways

Automated truck platooning has become an increasingly popular research subject, and its applicability to highways is considered one of the earliest possible landing scenarios for automated driving. However, there is a lack of research regarding the combination of truck platooning technology and truck lane management strategy on multilane highways in the environment of a cooperative vehicle–infrastructure system (CVIS). For highway weaving sections under the CVIS environment, this paper proposes a truck platooning optimal speed control model based on multi-objective optimization. Through a combination of model predictive control and the cell transmission model, this approach considers the bottleneck cell traffic flow, overall vehicle travel time, and truck platooning fuel consumption as objectives. By conducting experiments on a mixed traffic flow simulation platform, the multi-lane management strategies and optimal speed control effect were evaluated through different scenarios. This study also determined the appropriate proportion of truck platooning for an exclusive lane and to increase truck lanes, thus providing effective lane management decision support for highway managers.

Glycaemic control and novel technology management strategies in pregestational diabetes mellitus.

Pregestational diabetes (PGDM) is an increasingly common and complex condition that infers risk to both mother and infant. To prevent serious morbidity, strict glycaemic control is essential. The aim of this review is to review the glucose sensing and insulin delivering technologies currently available for women with PGDM. We reviewed online databases for articles relating to technology use in pregnancy using a combination of keywords and MeSH headings. Relevant articles are included below. A number of technological advancements have improved care and outcomes for women with PGDM. Real time continuous glucose monitoring (rtCGM) offers clear advantages in terms of infants size and neonatal intensive care unit admissions; and further benefits are seen when combined with continuous subcutaneous insulin delivery (insulin pump) and algorithms which continuously adjust insulin levels to glucose targets (hybrid closed loop). Other advancements including flash or intermittent scanning CGM (isCGM) and stand-alone insulin pumps do not confer as many advantages for women and their infants, however they are increasingly used outside of pregnancy and many women enter pregnancy already using these devices. This article offers a discussion of the most commonly used technologies in pregnancy and evaluates their current and future roles.

A Regression-Based “Patent Data Analysis” Approach: A Case Study for “Weapon Technology” Evaluation Process

Technology evaluation is one of the most essential tasks for today's companies to make correct decisions that will increase their competitiveness. To date, numeroushave been made to address technology evaluation in the literature. Nevertheless, none of them have built a technology map or classified technologies based on their effects on the competitive power of a company in practice. To overcome the limitations of previous studies, a regression-based patent data analysis is proposed here for technology evaluation in this article. To this end, the proposed approach builds a technology map and classifies the technologies into four classes with respect to the technology effect ratio, namely 1) very high effect class, 2) high effect class, 3) medium effect class, and 4) low effect class. The technology evaluation of weapon technology in the defense industry has been conducted to show how the proposed approach works in real life. A good technology management strategy can be selected among available alternatives by decision makers and managers using the proposed approach. The results show that the proposed technology evaluation process can be used effectively in practice.