WEEK 04 — DIGITAL TRANSFORMATION

TAM, UTAUT, IoT, Cloud, Edge, Fog

Agenda

  1. 1Discuss technology acceptance models: TAM, UTAUT
  2. 2Difference between IoT, Cloud, Edge, and Fog Computing
  3. 3Conclusion
  4. 4Q&A
Dr. Davood WadiDigital Transformation
A person in profile faces a framed screen holding a digital shop, with a red arrow from the person to the screen showing technology acceptance and use

CHAPTER 01

Technology Acceptance Model (TAM)

CLASS DISCUSSION

  1. 1Think of a time you adopted a new app or tool (e.g., TikTok, Zoom, ChatGPT, a fitness tracker). What specific factors convinced you to use it? Was it because it solved a problem quickly, was easy to learn, or because peers recommended it? If you avoided a tool (e.g., Twitter/X, a new software update), what turned you off?
  2. 2Did you care more about how intuitive it was or how much value it added? For example, did you stick with Instagram Reels because it felt familiar, or switch to TikTok for better features?
Two people in profile face each other, each with a speech bubble, in conversation

THEORETICAL FRAMEWORK

Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) is a theoretical framework that helps to explain and predict how users come to accept and use a technology.

Developed by Fred Davis in 1986, TAM is widely used in information systems research to understand user behavior regarding technology adoption.

The Technology Acceptance Model: External Variables point to Perceived Usefulness (U) and Perceived Ease of Use (E); Perceived Ease of Use points up to Perceived Usefulness; both point to Attitude Toward Using (A), which together with Perceived Usefulness points to Behavioral Intention to Use, leading to Actual System Use in redExternalVariablesPerceivedUsefulness (U)Perceived Easeof Use (E)AttitudeTowardUsing (A)BehavioralIntention toUseActualSystemUse

COMPONENTS OF TAM

Components of TAM: External Variables

External variables: Factors outside the model that influence perceived usefulness (U) and perceived ease of use (E).

  1. 1System Features:

    The functionality, design, and interface of the technology.

  2. 2User Characteristics:

    Age, education, prior experience, or computer self-efficacy.

  3. 3Social Influence:

    Peer pressure, organizational culture, or support from leadership.

  4. 4Training and Support:

    Availability of resources to help users understand the system.

  5. 5Task Characteristics:

    Complexity and relevance of the tasks the technology is designed to support.

SIMULATED. Five external variables on the left (1 System Features, 2 User Characteristics, 3 Social Influence, 4 Training and Support, 5 Task Characteristics) point to Perceived Usefulness (U) and Perceived Ease of Use (E) on the right; System Features is selected in red, setting U to 84% and E to 86%SIMULATED12345Perceived Usefulness (U)84%Perceived Ease of Use (E)86%1. System Features

COMPONENTS OF TAM

Components of TAM: Beliefs, Attitude, and Intention

1.Perceived Usefulness (PU):

  • The degree to which a person believes that using a particular technology will enhance their job performance or productivity.
  • If users perceive a technology as useful, they are more likely to adopt it.

2.Perceived Ease of Use (PEOU):

  • This is the degree to which a person believes that using a technology will be free of effort.
  • If a technology is easy to use, users are more likely to accept and utilize it.

Attitude Toward Use:

  • Determined by perceived usefulness and perceived ease of use
  • A positive attitude can lead to a higher likelihood of technology adoption.

Behavioral Intention to Use:

The attitude toward use affects the behavioral intention to use the technology.

SIMULATED. Interactive TAM sliders: Perceived Usefulness (PU) is set to 75% and Perceived Ease of Use (PEOU) is set to 70%, producing Attitude Toward Use of 72% and Behavioral Intention to Use of 73%SIMULATEDPerceived Usefulness (PU)75%Perceived Ease of Use (PEOU)70%Attitude Toward Use72%Behavioral Intention to Use73%
Exercise · Which one is it?

A commuter coffee shop launches a mobile pre-order app. Name which component of TAM each customer statement shows.

Ordering on the train saves me ten minutes every morning before work.

Which concept does this case show?

CHAPTER 02

Applications of TAM

CASE STUDY 01 — E-COMMERCE

Example: Application of TAM in E-Commerce

BestBuy is introducing a new AI-powered virtual shopping assistant to improve the online shopping experience.

The Technology Acceptance Model (TAM) can be applied to analyze how customers adopt this technology.

Four numbered external variable badges on the left (1 interface sliders, 2 a tech-savvy shopper, 3 a review star, 4 a tutorial document) point to a framed screen holding a digital shop and a red chat assistant bubble1234

External Variables

1.System Features:

The virtual assistant provides personalized product recommendations and fast responses.

2.User Characteristics:

Target audience includes tech-savvy millennials who are comfortable using AI-based tools.

3.Social Influence:

Online reviews and endorsements by influencers promote the virtual assistant.

4.Training and Support:

Tutorials and FAQs are provided to educate users on how to use the assistant.

TAM FOR BESTBUY

TAM for BestBuy: Adoption and Benefits

Perceived Ease of Use (U)

  • Do users believe the assistant is easy to interact with due to its intuitive chat interface?
  • Should we add voice commands?
  • How is adding more features reducing the ease of use?

Perceived Usefulness (E)

  • Do customers find the assistant helpful because it saves time by suggesting relevant products and streamlining the shopping process?

Attitude Toward Using (A)

Do positive perceptions of usefulness and ease of use lead customers to feel favorable toward using the virtual assistant?

Behavioral Intention to Use (B)

Because of their positive attitude, do customers intend to use the assistant in their future shopping activities?

Actual System Use

Over time, do users actively use the virtual assistant to explore and purchase products on the e-commerce platform?

Measuring Benefits of Technology

  1. 1.Increased customer satisfaction due to a smoother shopping experience?
  2. 2.Higher conversion rates as customers are more likely to complete purchases?
  3. 3.Enhanced brand loyalty as users find the platform innovative and user-friendly?
SIMULATED. Interactive feature trade-off for BestBuy's virtual shopping assistant: with 3 features on the screen, Perceived Usefulness is 88%, Perceived Ease of Use is 78%, and Actual System Use is 85%SIMULATEDSystem Features: 3Perceived Usefulness (E)88%Perceived Ease of Use (U)78%Actual System Use85%
Knowledge Check

An online electronics retailer adds twelve new comparison filters, live voice commands, and a warranty calculator into a single chat window for its virtual shopping assistant. Customers suddenly stop finishing their chats. According to the TAM analysis for BestBuy, what best explains this drop?

CLASS DISCUSSION — BESTBUY

Discussion & Research Questions

Discussion Questions

  1. 1How can perceived ease of use be improved for users who are less tech-savvy? (Minority group)
  2. 2What additional features could make the virtual shopping assistant more useful?
  3. 3How can social influence, such as peer reviews, be leveraged to encourage adoption?

Research Questions

4

What AI tool can be incorporated to give the chatbot access to BestBuy's product catalog and manuals?

Left: a product catalog database above a manual document. Center: a red arrow connects them into a framed screen holding a chat bubble and digital shop, facing a customer on the right

CASE STUDY 02 — HEALTHCARE

Example: TAM for AI Chatbots in a Hospital

A hospital adopts an AI-powered chatbot to assist patients in triage,

offering preliminary medical advice

determining whether they need urgent care or can manage their symptoms at home.

TAM can help evaluate how staff and patients accept this technology.

External Variables

1.System Features:

The chatbot uses natural language processing (NLP) to understand patient queries and provides accurate recommendations based on medical databases.

2.User Characteristics:

  • Patients may range from tech-savvy individuals to older adults with limited technology experience.
  • Nurses may initially feel skeptical about its reliability.
  • Medical doctors who feel threatened.

3.Social Influence:

Healthcare professionals and community leaders endorse the chatbot, increasing trust among patients.

4.Training and Support:

Hospitals offer tutorials and demos to help patients and staff navigate the chatbot.

Two patients in profile face a triage chatbot on a framed screen; from the screen, a black arrow leads to a house labeled At home, and a red arrow leads to a medical cross labeled Urgent careTriageAt homeUrgent care

TAM FOR AI CHATBOTS IN A HOSPITAL

TAM for AI Chatbots in a Hospital: Adoption and Benefits

Perceived Ease of Use (E)

Patients find the chatbot user-friendly because of its simple interface, quick responses, and ability to handle non-technical language.

Perceived Usefulness (U)

  • The chatbot reduces waiting times and improves patient outcomes by streamlining the triage process.
  • Medical staff find it useful as it filters non-urgent cases, allowing them to focus on critical patients.

Attitude Toward Using (A)

Both patients and staff develop a positive attitude toward the chatbot, appreciating its efficiency and time-saving benefits.

Behavioral Intention to Use (BI)

Due to their favorable attitude, patients and staff intend to use the chatbot regularly. Patients plan to consult it for initial assessments, while staff use its data to prioritize cases.

Actual System Use

The chatbot becomes widely used in the hospital, helping patients and supporting staff during peak hours or emergencies.

SIMULATED. Interactive hospital triage simulator: when the chatbot filters 65% of non-urgent cases, Waiting times drop to 41% and Staff focus on critical patients rises to 83%SIMULATEDNon-urgent cases filtered65%Waiting times41%Focus on critical patients83%

Benefits for the Hospital

1.Improved Patient Experience:

Patients receive quicker responses and guidance for their symptoms.

2.Optimized Staff Workload:

Staff focus on urgent cases, improving care quality.

3.Operational Efficiency:

Triage times are reduced, leading to better resource allocation.

Exercise · Sort into groups

A regional clinic rolls out an AI symptom-checker chatbot. Sort each item into External Variables, TAM Beliefs (Ease of Use & Usefulness), or Benefits for the Hospital.

        Tap a card, then tap the group it belongs to.

        CLASS DISCUSSION — HOSPITAL CHATBOT

        Discussion & Research Questions

        Left: a framed screen holding a patient health record document, labeled EHR. Center: a red arrow connects it into a second framed screen holding a chatbot bubble and medical crossEHR

        Discussion Questions

        1. 1How can hospitals ensure the chatbot's ease of use for elderly patients or those with limited digital literacy?
        2. 2What measures can be taken to build trust in the chatbot's reliability among medical staff?
        3. 3How might the chatbot’s usefulness increase if integrated with electronic health records (EHRs)?

        Research Question

        4

        What AI tool can help integrate electronic health records (EHRs) into the chatbot?

        CASE STUDY 03 — RETAIL SELF-SERVICE

        Example: TAM for IKEA’s Self-Return Kiosk

        IKEA has introduced a self-return kiosk at its stores

        Customers should process product returns without staff assistance.

        Let's apply TAM to understand how customers would accept this technology.

        External Variables

        1.System Features:

        The kiosk features

        • a touch screen,
        • clear instructions,
        • barcode scanner.

        2.User Characteristics:

        • Customers vary in their familiarity with self-service technologies,
        • from tech-savvy individuals to those who prefer in-person interaction.

        3.Social Influence:

        Other customers using the kiosk successfully influence hesitant users to try it.

        4.Training and Support:

        On-screen guidance and staff nearby to assist reduce apprehension among first-time users.

        Left: four customers waiting in line behind a counter, labeled Waiting in line. Right: a single customer steps directly to a framed screen holding a package and return arrow, labeled Self-return kiosk in redWaiting in lineSelf-return kiosk

        TAM FOR IKEA’S SELF-RETURN KIOSK

        TAM for IKEA’s Self-Return Kiosk: Adoption and Benefits

        Perceived Ease of Use (E)

        Customers find the kiosk intuitive due to its step-by-step instructions, visual aids, and quick processing time.

        Perceived Usefulness (U)

        • The kiosk eliminates waiting in line
        • This is particularly beneficial during peak hours.

        Attitude Toward Using (A)

        Customers to view the kiosk as an effective solution.

        Behavioral Intention to Use (BI)

        Customers intend to use the kiosk for future returns and may recommend it to others.

        Actual System Use

        Over time, the kiosk sees increased adoption, with customers actively using it for returns, leading to faster service times and reduced staff workload.

        Benefits for IKEA

        1.Enhanced Customer Experience:

        Faster returns process improves overall satisfaction.

        2.Operational Efficiency:

        Staff focus on complex issues while routine returns are handled by the kiosk.

        3.Cost Savings:

        Lower dependency on staff for simple returns reduces operational costs.

        Top: a framed kiosk screen holding a barcode and package points to a fast clock, labeled Faster returns. Bottom: a staff member works on complex gears beside a red stack of coins, labeled Cost savingsFaster returnsCostsavings
        Exercise · Put it in order

        A hardware store introduces a self-return kiosk. Put the customer's adoption journey in the order of the Technology Acceptance Model (TAM).

        Tap a step, then the number where it belongs.

        CLASS DISCUSSION — IKEA SELF-RETURN KIOSK

        Apprehensions & Discussion Questions

        Question

        Think about your own experience: when forced to use a new technology in public what types of apprehensions do you face? How can these apprehensions be alleviated?

        Discussion Questions

        1. 1What design elements can IKEA add to make the kiosk more accessible to older customers?
        2. 2How can IKEA promote the kiosk to customers hesitant about using technology?
        3. 3What features could make the kiosk even more useful (e.g., integrating loyalty rewards during returns)?
        Two people in profile face each other, each with a speech bubble, in conversation

        CHAPTER 03

        The Unified Theory of Acceptance and Use of Technology (UTAUT)

        Your company recently rolled out a new collaboration platform (e.g., Slack, Asana, or a mandatory AI tool). While TAM focuses on perceived usefulness and ease of use, what one factor outside of these two do you think most influenced adoption or resistance? For example, was it pressure from leadership, lack of training, or compatibility with existing workflows? Use a real-world case to argue why this factor mattered more than pure ‘usefulness’ or ‘ease of use’.

        Question

        Two people in profile face each other, each with a speech bubble, in conversation

        THEORETICAL FRAMEWORK

        The Unified Theory of Acceptance and Use of Technology (UTAUT)

        The Unified Theory of Acceptance and Use of Technology (UTAUT) is a theoretical framework developed to understand the factors that influence individuals' acceptance and use of technology.

        It was introduced by Venkatesh et al. in 2003

        integrates elements from several existing models of technology acceptance: Technology Acceptance Model (TAM), Theory of Planned Behavior (TPB), Motivational Model.

        Three prior models on the left (TAM, TPB, Motivational Model) converge into a central red block labeled UTAUT 2003, which branches into four numbered constructs (1 to 4) on the rightTAMTPBMotivationalModelUTAUT20031234

        Four primary constructs that significantly influence technology acceptance and usage:

        1.Performance Expectancy:

        How much the technology is perceived to enhance job performance.

        2.Effort Expectancy:

        This construct reflects the ease of use associated with the technology.

        3.Social Influence:

        How much individuals perceive that important others (e.g., peers, family, or colleagues) believe they should use the new technology.

        4.Facilitating Conditions:

        The resources and support available to individuals for using the technology: infrastructure, training, technical support.

        Exercise · Match up

        A law firm rolls out a new document-search platform. Match each primary UTAUT construct with what it captures at the firm.

        UTAUT Construct

        At the law firm

        Tap a term, then the example it goes with.

        UTAUT MODEL

        Moderating Variables

        What are moderators in a theoretical framework?

        Age:

        Different age groups may have varying levels of technology acceptance.

        Gender:

        Men and women may have different perceptions and attitudes toward technology.

        Experience:

        Prior experience with similar technologies can influence acceptance.

        Voluntariness of Use:

        Whether the use of the technology is mandatory or voluntary can affect acceptance.

        The UTAUT model (Venkatesh et al., 2003): Performance Expectancy, Effort Expectancy, and Social Influence point to Behavioral Intention, which together with Facilitating Conditions points to Use Behavior. Bottom row shows four moderating variables (Gender, Age, Experience, Voluntariness of Use); Experience is selected in red, highlighting the 3 paths it moderatesPerformance ExpectancyEffort ExpectancySocial InfluenceFacilitating ConditionsBehavioralIntentionUseBehaviorGenderAgeExperienceVoluntariness of Use

        CASE STUDY — UTAUT

        UTAUT for IKEA's Self-Return Kiosk

        Performance Expectancy

        Do customers believe the kiosk enhances efficiency by saving time and reducing waiting lines, especially during peak hours?

        Effort Expectancy

        Is kiosk is perceived as easy to use due to its intuitive touch screen, step-by-step instructions, and visual aids?

        Social Influence

        • Observing other customers successfully using the kiosk encourages hesitant users to try it.
        • Positive word-of-mouth promotes trust in the system.

        Facilitating Conditions

        • On-site support staff and clear guidance help users overcome technical or usability challenges.
        • Accessible design ensures inclusion for diverse user groups, such as those with limited technology familiarity.
        Four visual stations for IKEA's kiosk under the four UTAUT constructs: 1 a clock for saving time, 2 a framed touch screen for ease of use, 3 two shoppers talking for word-of-mouth social influence, and 4 a support staff member with a guidance document for facilitating conditions; arrows point down to the outcomes below

        Behavioral Intention

        Customers show an intention to use the kiosk in the future and to recommend it to others based on their experience.

        Actual Use

        Over time, increased confidence and trust lead to higher adoption rates, resulting in streamlined operations and reduced staff workload.

        UTAUT FOR IKEA'S SELF-RETURN KIOSK

        Moderating Variables

        1. 1Age:

          Younger customers may adopt the kiosk more quickly due to greater familiarity with technology.

        2. 2Gender:

          Gender may moderate attitudes, as studies show varying adoption rates across demographic groups.

        3. 3Experience:

          Experienced users adapt to the kiosk faster, while first-time users may rely more on guidance and staff support.

        4. 4Voluntariness of Use:

          If customers feel forced to use the kiosk (e.g., no alternative for returns), satisfaction and adoption rates may be impacted.

        5. 5Cultural Context:

          Acceptance may vary based on regional or cultural familiarity with self-service technology.

        SIMULATED. Interactive IKEA moderating variables: 4. Voluntariness is selected on the left, comparing kiosk adoption between Voluntary choice (84%) and Forced (no alternative) (42%) on the rightSIMULATED1. Age2. Gender3. Experience4. Voluntariness5. Cultural ContextVoluntary choice84%Forced (no alternative)42%Adoption & satisfaction
        Exercise · Which one is it?

        An airline installs self-service bag-drop kiosks at its terminals. Name which moderating variable from the IKEA UTAUT analysis explains each pattern.

        When the airline closes all staffed desks so flyers feel forced to use the kiosk, satisfaction scores drop sharply.

        Which concept does this case show?

        CHAPTER 04

        Introduction to IoT, Cloud, Edge, and Fog Computing

        INTERNET OF THINGS

        What is IoT?

        Internet of Things (IoT) refers to a network of interconnected devices that collect, share, and act on data.

        smart thermostats, wearable fitness trackers, and connected cars.

        Discussion Question

        How does IoT influence the way businesses interact with customers? Troubleshooting your fridge

        IoT network loop for Smart thermostats: Collect (the device gathers sensor data), Share (transmits data to a framed screen), and Act in red (automated control acts on the data)CollectShareActSmart thermostatsWearable fitness trackersConnected cars

        IOT PRIVACY AND SECURITY

        IoT Privacy and Security

        1.Implement strong device authentication:

        Use robust authentication methods like two-factor authentication, biometrics, or digital certificates, and avoid default or weak passwords.

        2.Secure network communications:

        Encrypt data transmitted between IoT devices and back-end systems using secure protocols (e.g., TLS/SSL) and segment IoT devices on separate networks.

        3.Keep software and firmware updated:

        Regularly update IoT devices with the latest security patches and enable automatic updates when possible to protect against known vulnerabilities.

        4.Limit data collection and storage:

        Collect and store only the minimum necessary data for the IoT device to function, and anonymize or pseudonymize sensitive data to reduce the impact of potential breaches.

        5.Educate users on IoT security:

        Provide clear guidelines and training to users on securely setting up, configuring, and using IoT devices, and encourage them to report suspicious activities or potential vulnerabilities.

        Five numbered security stations aligned across a rail: 1, a key inside a framed screen for device authentication; 2, a lock on a network link for secure communications; 3, an update cycle on a framed screen for firmware updates; 4, one kept data block beside two crossed-out blocks for limiting data collection; 5, a person with a red shield for educating users12345
        Exercise · Match up

        A hospital deploys connected patient-monitoring wristbands. Match each IoT privacy and security best practice with how the hospital applies it.

        Best Practice

        Hospital Action

        Tap a term, then the example it goes with.

        IIoT (Industrial Internet of Things)

        IoT Device Management Process

        1. 1.Provisioning and Authentication

        2. 2.Configuration and Control

        3. 3.Monitoring and Diagnostics

        4. 4.Software Updates and Maintenance

        5. 5.Decommissioning

        Five connected stages of the IoT device management process: 1 Provisioning and Authentication (a key), 2 Configuration and Control (sliders), 3 Monitoring and Diagnostics (a pulse line), 4 Software Updates and Maintenance (an update cycle), and 5 Decommissioning in red (a power symbol), with a return path under the row back to stage 1
        Exercise · Put it in order

        A cold-chain logistics company installs connected temperature sensors in its refrigerated trucks. Put the five stages of the IoT Device Management Process in order.

        Tap a step, then the number where it belongs.

        CLOUD COMPUTING

        What is Cloud Computing?

        Cloud computing delivers computing resources (storage, processing, and software) over the internet.

        Google Drive, Amazon Web Services (AWS).

        • scalability
        • remote access
        • central data center.

        Discussion Question

        What are the benefits and challenges of cloud computing for businesses?

        A central framed screen labeled Central data center holds a cloud, storage database, and processor; arrows connect it to remote people on the left and a remote business shop on the rightCentral data center

        DISTRIBUTED COMPUTING

        What is Edge & Fog Computing?

        What is Edge Computing?

        • Edge computing processes data near its source (e.g., on IoT devices or local servers).
        • Reduces latency and bandwidth usage,
        • critical for real-time tasks like autonomous vehicles.

        Discussion Question

        In what scenarios is edge computing preferred over cloud computing?

        What is Fog Computing?

        • Fog computing acts as a bridge between cloud and edge computing.
        • It distributes processing tasks across local networks (closer than cloud but farther than edge).
        • A factory uses fog to analyze machine data locally and send summaries to the cloud.

        Discussion Question

        How does fog computing complement both cloud and edge computing?

        SIMULATED. Interactive comparison of Edge, Fog, and Cloud computing: processing at the Edge tier shows the round-trip path from the data source and produces Latency of 14% and Bandwidth usage of 18%SourceEdgeFogCloudLatency14%Bandwidth usage18%SIMULATED

        ARCHITECTURE COMPARISON

        Disambiguating the Terms

        ConceptDefinitionUse Case
        IoTDevices connected to the internet that collect and transmit data.Smart home appliances
        CloudCentralized data storage and processing over the internet.Data analytics for e-commerce
        EdgeLocalized data processing at or near the source.Autonomous vehicles
        FogDistributed processing between cloud and edge, closer to the local network.Industrial IoT for manufacturing
        Interactive four-layer architecture stack (Cloud, Fog, Edge, IoT) on the left; Fog is selected in red, pointing to a framed screen on the right showing its use case: Industrial IoT for manufacturingCloudFogEdgeIoTIndustrial IoTfor manufacturing
        Exercise · Which one is it?

        A manufacturing group connects its factories and delivery fleet. Name whether each part of its architecture is IoT, Edge, Fog, or Cloud.

        Smart thermostats and vibration sensors mounted on assembly-line motors that collect and transmit readings.

        Which concept does this case show?

        CONCLUSION

        Conclusion

        KEY TAKEAWAYS

        1. 1Two models for technology acceptance (TAM, UTAUT)
        2. 2IoT
        3. 3Cloud, Fog, and Edge Computing