Data collection

ICETS Case

The ICETS case was conducted in the US. Data collection was primarily via semi-structured interviews, in person and over the phone. A qualitative survey was sent to team members to understand how they saw AR attributes and limitations. Secondary data collection was from annual reports, public interviews, YouTube videos, and other social media (Maimbo and Pervan, 2005) (Table 5). ICETS did not provide access to direct customer feedback, as that was not sharable. However, I could attend the co-creation sessions to observe and take notes. The response from the ICETS head on an AR design case using human-centered approaches was positive. This allowed me to have conversations on ICETS' scope and activity with AR, the partners they engaged with to build integrated solutions, and their capabilities to design different AR devices in varied retail settings.

The qualitative type of survey was used (section to determine the diversity of the use and charactersitics of the different AR displays available at ICETS within that team. This type of survey does not count the number of people with the same characteristic but it establishes the meaningful variation (relevant dimensions and values) within that group to understand what device is used for what purpose and why.

(Jansen, 2010). A list of questions in a survey format (Mackey, Cooling, and Berrie, 1984) was then sent to 30 ICETS team members. ICETS provided overviews and answered questions on its partners,

engagements, and capabilities to use for the case. Responses to the survey questions administered to their 30 engineering development and leadership staff were consolidated into themes using coding. The questions asked were informed by the underlying technology and the theoretical framework of the human-centered factors impacting the design and development of AR solutions.

Co-creation sessions

I attended the co-creation sessions (explained in Chapter 6) as an observer. This was to understand how the process worked, what the inputs were from the retailer and the customers, and how AR technology was selected to meet users' requirements and address the underlying problem use case. I was not provided access to engage with or have interviews with the retailer or the customer participants directly;

however, I had access to the artifacts created and asked interview questions to ICETS.

Table 5. Sources of data collection for ICETS case

Semi-structured interviews

The responses from the qualitative surveys were helpful in creating the interview guide for the semi-structured interviews (section 2.3.1). The case protocol and interview guide to conduct these interviews (Appendix 8) were centered around considering the human factors in designing AR solutions for the different clients. Three semi-structured interviews were conducted with the leaders of ICETS to understand how ICETS used the human-centered approach with their clients.

AVP, ICETS Head: The interview with the AVP as the overall head of ICETS was to understand the digital technologies they were engaged in, how they assessed the retailer's digital maturity, what were the different ways they determined the right solutions, including AR, and to understand the roles and

responsibilities of his organization. He was also accommodating in connecting me to the other interviewee, helping administer the survey, and validating the content that I produced.

Head of XR Labs, ICETS: The head sees things others don't, thanks to his 20-odd years working in the computer graphics field. He helped paint a better picture of augmented and virtual reality capabilities by showing how the technologies will impact consumers and professionals, how they'll buttress new and old industries, and what paths are necessary to get there.

Qualitative survey

The qualitative type of survey (Section 2.3.2) was used to determine the diversity of the different AR characteristics based on device type and use. This type of survey does not count the number of people with the same feature (value of a variable). Still, it establishes the meaningful variation (relevant dimensions and values) within that population using a pre-structured list of questions (Boyatzis, 1998).

Source of data Number of people Data Collection Method

AVP, ICETS Head 1 email. Interview, validation of content

Head of XR Labs 1 Interview, quotations

Principal Product Architect 1 Survey

Senior Designer (XR) 4 Survey

Technical Lead (XR) 4 Survey

XR Developers 18 Survey

Principal Architect - Emerging

Technologies and Innovation 1

Interview, survey

Press releases Quotation, research tidbits

Media reports Quotation, research tidbits

Youtube videos provided by Infosys Research use cases

The sample size for the survey was determined based on the degree of precision and differentiation in the ICETS group structure, ability to gain access to the named subjects in the team, the stratification of the subjects to get different viewpoints from their perspectives, and the ability to conform to the underlying theoretical framework (Appendix 9).

Other Sources: Data was collected from various sources like a press release, media reports, and social media content provided by ICETS, depending on the research focus needs (Maimbo and Pervan, 2005).

This data collection was adopted in all the studies to augment the primary data collection¹². Infosys Case

The Infosys case was conducted in the US. Data collection was primarily via interviews with their Human-Centered Design leader and Retail Technology leader to understand how they used human-centered approaches with the right actors to design and develop AR solutions to address specific retail customer experience needs. Interviews were done with an interview guide (re-used from the ICETS study).

Design thinking

I attended the Design Thinking (DT) workshop and engaged in the focus group interviews with the co-design and development participants using the DT approach (explained in Chapter 6). I was not

provided access to engage with or have talks with the users directly; however, I had access to the artifacts created and asked interview questions to Infosys.

Semi-structured interviews

The interview guide to conduct these interviews (Appendix 8) was centered around considering the human factors in the design of AR solutions for the different clients. Two semi-structured interviews

12The ICETS team provided the following additional data sources that were publicaly available:

• https://www.infosys.com/services/incubating-emerging-technologies.html https://www.infosys.com/newsroom/press-releases.html

• https://www.infosys.com/services/incubating-emerging-technologies/offerings/living-labs.html

• https://www.youtube.com/watch?v=V37c1sFaJzA

• https://youtu.be/6zFCqDDGXeU

were conducted with Infosys's leaders to understand how Infosys used the human-centered approach with their clients (section 2.3.1).

Head of Learning and Development, Infosys: The leader of the Design Thinking approach at Infosys was interviewed to provide a good understanding of how Infosys used the IDEO DT approach and modified it to ensure that human elements for design and development were used. The process included deciding the retailer's maturity in these techniques. It involved organizing workshops and content and setting up interviews to make the retailer aware of the AR technology and its characteristics and how it could help address the customer experience problem.

Retail Technology Leader, Infosys: The retail technology leader specifically focused on Next-Gen Technologies like AR, AI, etc. He noted how Infosys had realized the importance of DT workshops for a clear definition of the problem, solution options, and a clear roadmap with the right mix of technology and operational processes. AR is gaining more and more traction as companies are investing more in AR that is led by a well-structured DT approach. He also helped review the case content once the draft was completed.

Focus groups: I was an observer of this mode of data gathering. Focus groups were key for data gathering to draw upon respondents' attitudes, feelings, beliefs, experiences, and reactions in a way that would not be feasible using other methods, for example, observation, one-to-one interviewing, or questionnaire surveys. The Respondent-Moderator format was used, where one of the group participants takes the lead as a moderator. Having one of the participants lead the discussion is thought to impact the group's dynamics by influencing participants' answers, thereby increasing the chances of varied and more honest responses (Kamberelis and Dimitriadis, 2005). It was done to change the dynamics of the group and generate more varied responses. The focus group setting enabled me to gain a large amount of information in a short period. The right mix of the luxury retailer, Infosys, and a few of their customers at the initial stages facilitated the definition of the problem, the expectations, and how those expectations could be fulfilled (Appendix 10). The participants' varying inputs and explanations were organized into themes and used to drive the DT workshops (Appendix 11) to design the iterations needed to co-develop the AR solutions.

Observations: A type of naturalistic observation was used to observe participants in this case. It enabled me to map how participants engaged with Infosys to co-design, the questions they asked, and how they accepted the technology as retailers or customers. I conducted observations given that Infosys did not provide direct access to the retailer and the customers based on the case's specifics. During the Infosys focus group discussions, the primary data collection methods included notetaking and participant observation (Stewart, Shamdasani, and Rook, 2007).