James Alstott

DB FPX 9803 Assessment 3 Project Results Data Collection and Analysis

DB FPX 9803 Assessment 3 Project Results Data Collection and Analysis

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DB FPX 9803 Assessment 3 Project Results Data Collection and Analysis Student Name Capella University DB-FPX9803 Project Results Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Table 1. Participant Demographics Participant Title Industry Retail experience (years) Leadership experience (years) Region P1 Manager Online fashion 3+ 3+ U.S. P2 Manager Online fashion/retail 3+ 3+ U.S. P3 Manager (unnamed) Online fashion 3+ 3+ U.S. P4 Manager (unnamed) Online fashion 3+ 3+ U.S. P5 Mid-level manager Online fashion/retail 3+ 3+ U.S. P6 Quality assurance manager Online retail (health, beauty, electronics) 3+ 3+ U.S. P7 Manager (compliance & anti-counterfeit) Online retail (fashion, consumer goods) 3+ 3+ U.S. P8 Founder E-commerce (electronics, lifestyle) 3+ 3+ U.S. P9 Manager Online retail (fashion, consumer goods) 3+ 3+ U.S. P10 Operations manager Online retail (electronics, health, fashion) 3+ 3+ U.S. P11 Founder/manager Online retail (multiple industries) 3+ 3+ U.S. Note. Table 1 shows participant demographics for each interview. Table 2. Participant Interview Overview ID Duration (Approx.) Eligibility Inclusion/Exclusion for Coding P1 ~15 minutes Meets all criteria Not Included Lack depth, narrative rigor. The point of saturation happened after interview P9. Thematic coding was entirely performed with the help of nine transcripts (P3-P11) but P1 and P2 were to be utilized in procedural documentation. P2 ~13 minutes Meets all criteria Not Included Are not so rigorous in either depth or narrative. At the interview P9, the information saturation was attained. Nine transcripts (P3 -P11) and 1 and 2 were fully coded thematically and stored to serve as procedural documentation. P3 ~11 minutes Meets all criteria (Manager, 3+ years, Anti-CF exp.) Included – Full responses relevant P4 ~10 minutes Meets all criteria Included – Sufficient relevant content P5 ~12 minutes Meets all criteria Included – Detailed operational info P6 ~16 minutes Meets all criteria Included – Rich technical data P7 ~13 minutes Meets all criteria Included – Strong thematic alignment P8 ~13 minutes Meets all criteria (Founder, Cybersecurity background) Included – High relevance P9 ~13 minutes Meets all criteria Included – Complete, usable interview P10 ~15 minutes Meets all criteria Included – Extensive insight provided P11 ~13 minutes Meets all criteria (5+ years, Founder) Included – Thematic relevance confirmed Note. Table 2 represents the participant interview overview. Table 3. Initial Code Development and Refinement Section Code category Initial Code Definition Supporting Quote Final refined code Technological challenges Detection limitations Difficulty in identifying counterfeits Challenges in detecting counterfeit goods using existing tech or manual means. “Even though we have strong controls, it’s impossible to check every single product and seller…” (P11) Technological limitations in detection Technological challenges Integration issues Difficulty integrating new tools Complications arise from implementing or aligning new technology with existing systems. “Sometimes, you know, it takes time to integrate these new tools and systems into our operations fully.” (P11) System integration constraints Impact on revenue Lost sales & conversions Revenue loss due to counterfeits Financial impact on sales and conversion rates caused by counterfeits. “It probably costs us about 25% of our conversions… a couple million.” (P3) Sales revenue loss Impact on revenue Customer churn Losing repeat customers due to distrust Counterfeit experiences reduce customer trust and repeat buying behavior. “Customers who have encountered counterfeit issues are 72% less likely to return for additional purchases.” (P7) Customer retention decline Regulatory approaches Legal compliance gaps Weak or unclear regulations Lack of sufficient legal frameworks or enforcement to support anti-counterfeit efforts. “Clearer legal provisions and stronger enforcement of law… are essential.” (P9) Regulatory enforcement needs Regulatory approaches Collaborative frameworks Need for shared industry standards Importance of cross-platform regulatory collaboration and data sharing. “A shared database updated in real time across major e-commerce platforms… would serve as an early warning system.” (P10) Industry-wide collaboration imperative Note. Table 3 shows the initial code development and refinement of the project. Table 4. Categories and Aligned Codes Section Category Definition Contributing refined code Supporting Pattern Evidence Technological challenges Detection limitations Limitations in accurately identifying counterfeit goods using current systems. – Technological limitations in detection Participants reported difficulty verifying authenticity due to sophisticated counterfeit packaging (P6, P8, P11). Technological challenges Integration issues Barriers to effectively implementing new technological systems. – System integration constraints Mention of delays and operational disruptions during tool adoption or system syncing (P6, P10, P11). Impact on revenue Lost sales & conversions Revenue loss due to customers unknowingly buying counterfeit goods or leaving the platform. – Sales revenue loss Direct losses are estimated in millions due to lost conversions (P3, P10). Impact on revenue Customer churn Customers stop buying after encountering a counterfeit due to broken trust. – Customer retention decline Patterns of decreased repeat purchases and lower post-purchase engagement (P7, P9, P11). Regulatory approaches Legal compliance gaps Inadequate laws or enforcement to deter counterfeit distribution. – Regulatory enforcement needs Calls for clearer rules and more support from legal frameworks (P9, P10). Regulatory approaches Collaborative frameworks Necessity for shared standards and cooperation across companies/platforms. – Industry-wide collaboration is imperative Emphasis on shared databases and joint enforcement practices (P10, P6). Note. Table 4 shows how categories are aligned with the codes. Table 5. Themes from Analysis Theme Participant quote Definition Technological challenges and solutions in combating counterfeit products to protect revenue “Fake electronics are so good now that just looking at them isn’t enough… we had to add automation and better detection tools.” – P8. Such theme means the shortcomings of the conventional means to detect fake products and the shift to the new sophisticated technologies in order to preserve the authenticity and efficiency of functioning.   “We use AI-powered systems to detect and flag unusual inventory behaviors that may indicate counterfeit activities.” – P6. To beat the advanced level of counterfeit, companies adopt multi-layered technologies such as AI, QR codes, and digital verification tools to defend the brand image. Impact of counterfeit products on revenue and market share “It probably costs us about 25% of our conversions… a couple million.” – P3 This theme is a first hand manifestation to the actual financial implications of fake products, such as revenue and market share loss and customer trust and loyalty.   […]

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DB FPX 9801 Assessment 4

DB FPX 9801 Assessment 4

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DB FPX 9801 Assessment 4 Pre-Implementation Conference Call Presentation Student Name Capella University DB-FPX9801 Proposal Writing Professor Name Submission Date [blur_section id=”postDownload” button=”Free Download” form_id=”e9df100″] Slide 01 Pre-Implementation Conference Call Presentation Hello, my name is _________, and I came to see you today to deliver a pre-implementation conference call presentation on the idea of integrating a transformational leadership approach and using digital technologies to reduce supply chain disruptions. Slide 02 Introduction The current competition and high rate of globalization in the global markets has made the global markets extremely competitive. These dynamics have resulted in lean supply chain operations such as just-in-time and proper scheduling (Katsaliaki et al., 2021). Nevertheless, these plans make it harder and more disruptive (Deep et al., 2025). The U.S. supply chains are challenged by such problems as pandemics, shortage of labor, and geopolitical tension. A large number of managers do not have transformational leadership and risk management tools digital (Dura et al., 2025). The out-of-date systems lead to delays, inventory shortages, and demoralization (Alicke and Foster, 2024). The leaders are required to be resilient by adopting transformational leadership and using digital technologies. Slide 03 Statement of the Problem Problem Statement The overall business issue is that supply chain industry businesses have become more susceptible to supply chain disruptions, therefore amplifying the operational and financial cost of supply chain disruptions (Katsaliaki et al., 2021). The issue under concern is that not all supply chain managers in the U.S. have sound supply chain risk management principles and information technologies to create the supply chain resiliency, which leads to the decline of operational efficiency and employee motivation during disruptions (Deep et al., 2025). Purpose Statement The qualitative inquiry project aims to examine the views of supply chain managers in the U.S. regarding the application of transformational leadership and digital technologies as a means of creating organizational and workforce resilience in case of a supply chain disruption. Gap in Practice The practice gap is that U.S. supply chain managers do not have evidence-based approaches to integrating transformational leadership and utilizing digital technologies to achieve resilience of operations and workforce in case of disruptions in the supply chain (Yeboah et al., 2025). Slide 04 Theory(s) Supporting Research Figure 1 Visual Representation of Project Framework (Munir et al. 2020). The project theoretical framework is founded on Munir et al. (2020) and incorporates the supplier, consumer, and internal coordination. The internal integration is considered as the most successful risk management approach when the supply chain has been disrupted. The framework is focused on information processing power, which allows firms to collect and process information of suppliers and consumers. Nevertheless, internal integration is not enough in the current unstable world. The framework also includes transformational leadership that puts emphasis on visioning, empowering, and innovating (Taseer & Ahmed, 2022). Is also compatible with the dynamic capability theory, which emphasizes the capacity of an organization to change (Ayaz, 2022). Better control, planning, and predictive decision-making are supported with the help of technological factors, in particular, AI tools (Dura et al., 2025). The tools increase efficiency and velocity in supply chains. Workforce training and collaboration are essential to human resource development, which is critical in creating resilience (Saeed et al., 2022). The model links leadership, technology, and integration to develop a strong and flexible supply chain system. Slide 05 Methodology The generic qualitative inquiry technique is one of the most appropriate techniques of research that uncovers detailed information about the lived experiences of the participants in terms of their behaviors and choices made when facing a disruptive occurrence in the supply chain. The paper is grounded on the necessity of studying how U.S. supply chain managers can combine the idea of transformational leadership with digital technologies to create resiliency. The generic qualitative inquiry is aimed at knowing the how and why of the deployment of particular strategies in the complicated high-risk setting, particularly where numeric data cannot reproduce the entire picture (Creswell and Poth, 2018). The method is a flexible yet strict framework of studying rich, contextualized human experiences affirming the problem and purpose of the study Yeboah et al., 2025(Yeboah et al., 2025). The consistency of the research objectives with the research methodology also denotes that the study will capture finer viewpoints and adaptive behaviors that are important in supply chain resilience. Slide 06 Sample The study will target supply chain managers of the middle and senior level, who will be located in the United States, and work in various industries including manufacturing, logistics, retail, and healthcare. The sample consists of those who have been in charge of supply chain management and experienced disrupted supply chain management through the application of leadership or digital technology (Palinkas et al., 2015). The participants will enhance validity of the results since the individuals will present expert, experience-based views pertaining to the research questions. The purposive sampling will be applied to select intentionally the ones with the direct experience in disruption management to ensure that they are relevant and in-depth (Palinkas et al., 2015). The sample size will consist of 12 to 15 participants so that it becomes manageable yet the data saturation can be attained as a minimum of 10 finished interviews. Slide 07 Data Collection The proposed data collection tool includes semi-structured interviews to understand the application of transformational leadership and digital technologies by supply chain managers in the United States in case of disruption. The interviews will be carried out online through Zoom to provide the concept of flexibility and availability anywhere throughout the U.S. The participants will be those with 10+ years of experience and will be a part of the study. The interview guides will consist of 10 open-ended questions that are consistent with the digital resilience frameworks and transformational leadership theory (DeJonckheere and Vaughn, 2019). The audio-recorded data will be transcribed literally by means of the Otter.ai, and the finished version will be checked manually. Furthermore, thematic analysis will be utilized as the main means of determining the patterns of responses. The interviews will last approximately 45 60 minutes. Member-checking and peer debriefing will be used to assure reliability as accuracy and interpretation will […]

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DB FPX 9801 Assessment 6 Pre-Implementation Conference Call Presentation

DB FPX 9801 Assessment 6 Pre-Implementation Conference Call Presentation

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DB FPX 9801 Assessment 6 Pre-Implementation Conference Call Presentation Student Name Capella University DB FPX 9801 Professor Name Submission Date Slide 01 Pre-Implementation Conference Call Presentation Hello! My name is _______, and today, I would like to deliver a pre-implementation conference call presentation on the subject of adaptive leadership practices to digital transformation in medium-sized technology companies. Slide 02 Introduction Digital transformation plays the key role of competitive advantage and efficiency. Middle-sized technology companies are experiencing very specific challenges in digital transformation and hurdles (Ameen et al., 2022). The usual obstacles are the lack of resources and resistance to change among the employees (Ramesh & Delen, 2021). A large number of companies do not have digital capabilities and the latest technological infrastructure (Hojnik & Huđek, 2023). This approach can also help organizations align their digital initiatives with evolving business needs. Very few of them view digital transformation as a strategy. Adaptive leadership promotes innovation and decreases the rate of employee resistance (Chughtai et al., 2023). The project leaders investigate the adaptive leadership in the context of the success of transformation in mid-sized technology companies. Slide 03 Statement of the Problem Problem Statement The overall business issue is that majority of organizations cannot handle complex digital transformational technologies that lead to lower operational efficiency, lack of employee engagement and inability to meet strategic goals (Ameen et al., 2022). The targeted business issue is that leaders of the US mid-sized technology companies have problems with implementing leadership strategies that will help them overcome the employee resistance to digital change and achieve better competitiveness and growth opportunities (Skare et al., 2023). Purpose Statement The qualitative inquiry project is aimed at investigating the insights of leaders in the middle-sized US technology companies about the leadership strategies that can be employed to address employee resistance to digital transformation technologies. Gap in Practice The practice gap is that, very little is known about how leaders in mid-sized technology companies in the US perceive and use leadership strategies to overcome employee resistance to digital transformation technologies and lead to unsuccessful implementation projects and lost competitive advantages (Errida and Lotfi, 2021). Slide 04 Slide 05 Theory(s) Supporting Research The basis of the research is transformational leadership theory, which examines the effects of leadership on change and innovation in the organization. The transformational leadership theory discusses the significance of leadership in bringing about change in an organization. Burns proposed a model of leadership that has shared values, motivation and purpose (Burns, 1978). Bass extended the theory of Leadership of Burns in addition to behavioral leadership, which was measurable (Bass, 1985). Core transformational behaviors are determined by the four 4I dimensions or idealized influence, inspirational motivation, intellectual stimulation, and individualized consideration (Bass and Avolio, 1994). Idealized influence entails the leaders as role models of ethics and the development of trust (Burns, 1978). Inspirational motivation aims at explaining a common vision and motivating employees to act (Peláez et al., 2023). The stimulation of intellect stimulates novelty and contravening the norm (Burns, 1978; Schiuma et al., 2024). Individualized consideration involves mentoring, coaching, and consideration of individual developmental needs (Trenerry et al., 2021). Transformational leadership promotes the adaptive thinking in the context of technological change (Rahi et al., 2021). The theory is especially applicable in changing business environments where digital transformation plays an important role as a crucial competitive advantage. The theory facilitates digital literacy and readiness to change amongst mid-sized firms. The theory has developed to deal with virtual teams and digital innovation. The influence on the success of digital transformation was supported by Peláez et al. (2023). Contemporary researchers discover that there is a close correlation between the transformational behaviors and the innovation results (Schiuma et al., 2024). Leadership behavior has an impact on the use of digital tools and technologies. Transformational leadership is very appropriate in leading mid-sized firms through the transformation process. Slide 06 Methodology The generic qualitative inquiry technique is one of the most appropriate techniques to be used in research since it exposes the perspective of leadership on adaptive practices in the digital transformation environment. The paper is founded on qualitative research that makes it possible to analyze the subjective perceptions of individuals (Sekar and Bhuvaneswari, 2024). Generic qualitative inquiry helps to describe complex, situation-specific knowledge of the participants based on their lived experiences, and this approach suits the leadership studies (Fischer and Guzel, 2022). The method is flexible and allows an in-depth examination of adaptive leadership practices (Olatunde & Olenik, 2021). The consistency of the research goals and the methodology leads to subtle understanding of the leadership tactics in technological change processes. Slide 07 Sample The study target population is the leadership that is involved in the digital transformations in the organizations. The participants will consist of the CEOs, CTOs, and managers of digital transformation (Campbell et al., 2020). The participants will enhance the generalization and the perception of leadership in various industries. The participants will be sampled by the purposive sampling because they have a first-hand experience of digital transformation. The number of participants will be 10 so that the data collection process will be manageable and the researcher will be able to obtain in-depth insights into the behavior of the participants. Slide 08 Can you tell me about your current role and how long you have been in leadership positions within the technology sector? How would you describe your organization’s approach to digital transformation over the past few years? What specific leadership strategies have you found most effective in addressing employee resistance to digital transformation technologies? Can you describe a situation where you successfully overcame significant employee resistance to a digital initiative? What approach did you take? How do you identify early signs of employee resistance to new technologies, and what is your initial response? What communication strategies do you use when introducing new digital technologies to your team? How do you involve employees in the decision-making process for digital transformation initiatives? Can you describe how you build trust with employees who are hesitant about technological […]

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DB FPX 9801 Assessment 9

DB FPX 9801 Assessment 9

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DB FPX 9801 Assessment 9 LEVERAGING ARTIFICIAL INTELLIGENCE FOR STRATEGIC DECISION-MAKING IN HEALTH CARE by Student Name Professor Name Maja Zelihic, PhD, Dean Academics and Doctoral Studies School of Business, Technology and Health Care Administration A Capstone Work Presented in Partial Fulfillment Of the Requirements for the Degree Doctor of Business Administration Strategy and Innovation Capella University Month & year of dean’s approval   Professional Development Plan I could be a doctoral researcher working in the field of AI implementation in healthcare, which is why my opportunities to develop according to Applied Research Competencies are high and multidimensional. The multifaceted nature of the healthcare AI adoption, in light of the fact that only 25% of executives admit to realising potential of AI, despite a 75 percent recognition (Bain & Company, 2024) states the necessity to establish sophisticated research capabilities. Of course, these three sub domains are qualitative research method, analysis of the results and the distribution of the research findings. As to particular research methodologies, I am looking forward to acquiring high-level skills in semi-structured interviews and thematic research, as they will play a critical role in the scenario in which the proposed topic is applied due to the knowledge of the technology and the nature of the organization (AlKuwaiti et al., 2023). As far as data analysis is concerned, I will build my competence in terms of the organizational data about AI deployment since most healthcare organizations report problems related to data integration; on average, 40 percent of these institutions list data standardization among the systems among their issues (Hummelsberger et al., 2023). The research dissemination subdomain aims to provide adequate dissemination and presentation of the findings to the audience of various other stakeholders as the authorities of healthcare need this information to design the appropriate strategies and implementation procedures (Steerling et al., 2023). Figure 1 Professional Development Matrix The strategies that I intend to implement involve creating a classical structure of my work that will encompass the academic part and the practical part that is focused on achieving the goals, mechanisms that will assist me to be motivated and conquer difficulties. To enhance the quality of this practice, I will engage in communication with more advanced researchers and enroll in special methodology classes, such as interview strategy and thematic analysis of the work as it is conducted in the latest researches in the sphere of healthcare technology (Rahman et al., 2024). Regarding data analysis competencies, I will seek job placements in healthcare organisations that are also implementing AI solutions to analyse data in order to improve the analytical skills of the person undertaking the process as demonstrated by Krishingan et al., 2023. To a certain degree this model of development has already impacted my professional practice, since it encouraged me to become more involved in various types of activities, e.g. working on AI-implementation projects, collaborating with healthcare-technology teams. These exercises assisted me in the process of getting acquainted with utilizing various data sets to examine and synthesize the relevant to the fact that the healthcare organizations implementing AI solutions decrease the costs of operations by 25-30 percent (Rojek et al., 2023). The framework has also improved my skill to develop viable solutions to significant challenges in healthcare AI deployment, in particular, the problems related to data integration and change management, which are some of the critical impediments to successful implementation as Dwivedi et al. (2021) recognize. Conclusion According to this professional development model, I have outlined the plan in terms of developing the applied research competence to deal with the challenge of AI application in healthcare. Such competencies of merging qualitative research techniques, data analysis, and research communication capabilities equip me with the task when applied in the area of healthcare technology adoption. These research competencies enhancements will prove very helpful when healthcare organizations move to the direction of AI development. These skills will be applicable in making sure that the knowledge acquired through the organizational practice is reflected back in the healthcare academia to be analyzed further. The accumulation of these skills as thoroughly organized as well as the practical training opportunities in practice are more than good in terms of enriching my academic along with professional training as a healthcare AI practitioner. References AlKuwaiti, A., Nazer, K., AlReedy, A., AlShehri, S., AlMuhanna, A., Subbarayalu, A. V., Al Muhanna, D., & AlMuhanna, F. A. (2023). A review of the role of artificial intelligence in healthcare. Journal of Personalized Medicine, 13(6), 951. https://doi.org/10.3390/jpm13060951 Bain & Company. (2024). Majority of health system executives believe generative AI will reshape the industry, yet only 6% have a strategy in place. Bain. https://www.bain.com/about/media-center/press-releases/2023/majority-of-health-system-executives-believe-generative-ai-will-reshape-the-industry-yet-only-6-have-a-strategy-in-place/#:~:text=Press%20release- Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., & Medaglia, R. (2021). Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice, and policy. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2019.08.002 Hummelsberger, P., Koch, T., Rauh, S., Dorn, J., Lermer, E., Raue, M., Matthias, F., Schicho, A., Colak, E., Ghassemi, M., & Gaube, S. (2023). Insights on the current state and future outlook of artificial intelligence in healthcare from expert interviews. Journal of Medical Internet Research  Artificial Intelligence. https://doi.org/10.2196/47353 Krishnan, G., Singh, S., Pathania, M., & Dhar, M. (2023). Artificial intelligence in clinical medicine: Catalyzing a sustainable global healthcare paradigm. Frontiers in Artificial Intelligence, 6(6), 8–12. https://doi.org/10.3389/frai.2023.1227091 Rahman, Md. A., Victoros, E., Ernest, J. T., Davis, R., Shanjana, Y., & Islam, Md. R. (2024). Impact of artificial intelligence (AI) technology in healthcare sector: A critical evaluation of both sides of the coin. Clinical Pathology, 17. https://doi.org/10.1177/2632010×241226887 Rojek, I., Piechowski, M., & Mikołajewski, D. (2023). An artificial intelligence approach for improving maintenance to supervise machine failures and support their repair. Applied Sciences, 13(8), 4–11. https://doi.org/10.3390/app13084971 Steerling, E., Siira, E., Nilsen, P., Svedberg, P., & Nygren, J. (2023). Implementing AI in healthcare-the relevance of trust: A scoping review. Frontiers in Health Services, 3(3), 12–50. https://doi.org/10.3389/frhs.2023.1211150

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