This project designs an App for culture and heritage awareness, appreciation, transmission, and preservation. This is accomplished through the use of Double Diamond Model as the guiding framework for ideation. Within the different phases of the DDM, several technology management frameworks and techniques are also employed to explore and define problems, and generate solutions.

In Phase 1, data are collected through interviews, mind mapping, and research to ascertain problems and opportunities in the culture and heritage industry. The result of Phase 1 is a list of entries tagged based on its influence on the culture and heritage industry as positively influencing, negatively influencing, or both.

In Phase 2, these data are then organized and simplified into more defined entries. While there are numerous existing initiatives and promising opportunities in the industry, it is noticeable that majority of the entries are long-standing problems and challenges. Entries were categorized further based on how they affect the culture and heritage industry in the Philippine context. The entries range from more fundamental issues such as colonial mentality to technological issues such as lack of data. These entries are then filtered in terms of their viability for App execution. Viable entries are mostly challenges and opportunities that relate to the problem of culture and heritage awareness and appreciation, particularly on the depth of knowledge in Filipino culture and identity.

In Phase 3, solutions are generated based on the identified challenges and opportunities. For each set of entries, corresponding solutions are ideated. Some solutions overlap to solve various identified problems. These solutions are then materialized as features and content of the designed prototype of the App.

This project concludes with realizations on the numerous impact and benefits of the App to the culture and heritage industry, and recommendations on App development and commercialization.

This study, Development of Community of Practice (COP) Maturity Model, Roadmap and Work Plan for IT Delivery Engineering Productivity, Quality, and Collaboration, focuses on the recommendation of the establishment of a Community of Practice for IT Delivery Organizations specifically for Engineering Productivity, Quality, and Collaboration.

In the study, the researcher used the Community of Practice Success Wheel as a reference tool for creating a recommended Community of Practice. Various technology management concepts and frameworks were applied such as technology audit and benchmarking for assessment and baselining for the IT Delivery COP Roadmap, technology transfer, and adoption for the creation of the IT Delivery COP Work Plan. The researcher also employed the Capability Maturity Model Integration index in determining the IT Delivery COP Maturity Model.

The COP Roadmap was used as a guide for key activities and milestones along with recommended timelines for the establishment of the Community of Practice. The COP Work Plan introduced activities referenced from the People, Process, and Technology framework as these three elements need to work in harmony for a complete implementation plan to succeed. Lastly, the COP Maturity Model identified a baseline of processes, behaviors, and characteristics of an IT Delivery Engineering Productivity Community of Practice. It was used for gap analysis and improving teams’ maturity from Maturity Level 0 to achieve the target Maturity Level.

All in all, these tools were created to ensure the success of a Community of Practice once it is implemented in an IT delivery engineering organization focusing on productivity, quality, and collaboration.

The Food Technology (FT) profession plays a significant role in addressing food-related issues (i.e., food security, food safety, food availability) as well as the overall economic growth of the Philippines. Recent developments that could impact the profession such as the implementation of the Philippine Food Technology Act (RA 11052) and emergence of newer technologies emphasizes the need to investigate the profession further and how it will go moving forward in terms and innovations.

The study involved a stakeholder survey covering perceptions and expectations of FT students, graduates, and potential employers towards the profession in the context of RA 11052 implementation. The result of the survey was then used as part of the environmental analysis conducted in a ten (10)-stage scenario driven technology foresight. A total of fifteen key predictable variables (KPVs) and ten critical uncertainties (CUs) clustered into three (e.g., factors directly affecting human capital, factors related to current trends and events, factors encouraging good governance, partnerships, and collaboration) were identified to have an effect on the focal issue of the study.

The developed grand scenario showed that innovation in the FT profession in the Philippines may be driven further through improved labor force, streamlined government laws and regulations, and effective international collaborations and linkages. Recommendations were formulated based on the grand scenario including (1) maximizing the rights and privileges of professional food technologists (PFTs) under RA 11052, (2) adopting currently advanced technologies in the profession, (3) reviewing existing government laws and regulations, and (4) initiating more activities encouraging the collaborations between academic institutions, government, and industry both locally and internationally. Key findings from the study may be useful as a basis in formulating revisions when it comes to policy making related to the FT profession.

The emergence of Artificial Intelligence (AI) holds significant implications for various industries, notably in the industry call centers. This study focuses on a scenario-building initiative to go into the prospective futures of the Call Center Industry in the Philippines, with a focal point on the year 2028. As AI continues its evolution, a pivotal question arises: how will its widespread adoption influence the trajectory of the call center sector in the Philippines?

This study centers on the core issue of solving future scenarios for the Call Center Industry in the Philippines amidst the growing impact of Artificial Intelligence. The research involves identifying and evaluating factors that may reinforce or hinder the industry's advancement, creating a comprehensive portrayal of the likely landscape by 2028. The primary objective is to interpret how the integration of AI will change the industry's dynamics, given: What potential challenges might the Philippine call center industry face in an AI-dominated landscape?

This research has three main objectives: firstly, to thoroughly understand the factors affecting the future of the call center industry with the rise of AI; secondly, to create story-like scenarios imagining how AI could be integrated into the Philippine Call Center Industry by 2028; and finally, to carefully assess the consequences and weaknesses in these scenarios. By achieving these goals, the study aims to provide decision-makers with useful tools to navigate the changing landscape and promote a call center industry that can adapt and thrive.

The research introduces three distinct scenarios—SMARTS, ACCELERATE, and EPILOGUE—each portraying a different story for the future of the call center industry. SMARTS highlights the importance of enhancing workforce skills, imagining a future where Filipino call center professionals progress alongside AI. ACCELERATE positions the Philippines as a leader in AI innovation through cooperative learning and research centers. EPILOGUE takes a proactive stance in creating policies, aiming to establish the country as a global leader in ethical AI governance. These scenarios highlight the diverse challenges and opportunities, emphasizing the need for an integrated approach that includes workforce adaptation, research and development, and ethical AI governance to ensure a flourishing and competitive call center industry.

The food industry operates within a turbulent landscape characterized by perpetually evolving consumer demands (e.g., shifting dietary trends, rising health consciousness, clamor for sustainability) and intensifying competition from both established and emerging brands resulting in a multitude of new product launches globally. This volatility necessitates constant innovation and agility in new product development (NPD) processes. AI presents itself as a potential catalyst for enhancing early-stage NPD, particularly in crucial areas like market research and idea generation. As AI rapidly evolves, AI chatbots emerge as potential tools to enhance early-stage NPD, particularly in market research and idea generation. This capstone project investigates the technological acceptance of AI chatbots (focusing on Google Bard) among selected NPD professionals of a local food manufacturing company with an active R&D department. Through a mixed-method approach encompassing process review and conducting an AI chatbot exercise, the study explores (1) key opportunities and gaps; (2) the extent to which the selected individuals utilize internet-based services for market research and ideation, and their perception of their effectiveness; and (3) the level of acceptance and perceived usefulness of AI chatbots for early-stage NPD. Findings reveal a cautious optimism towards AI chatbots, acknowledging their potential benefits in data analysis, insights generation, and creative brainstorming while recognizing concerns regarding data accuracy, transparency, and potential bias. The study underscores the need for future research and development focused on enhancing data transparency, mitigating bias, and fostering human-AI collaboration to ensure the responsible and effective integration of AI chatbots within the food industry's NPD processes. By addressing these challenges and harnessing the potential of AI, the food industry can navigate the volatile market landscape and unlock innovative new product offerings for consumers. Additionally, the exploratory nature of the project which focused on a single AI chatbot (Google Bard) as a specific example serves as a valuable case study but also acknowledges the limitations of this approach such as the limited generalizability of the findings, suggesting further exploration of diverse AI tools and their potential applications in NPD.