On the role of technology adoption in enhancing workflow efficiency : A Case Study of an R&D Organization
Bani Ali, Sepideh (2025)
2025
Tuotantotalouden DI-ohjelma - Master's Programme in Industrial Engineering and Management
Johtamisen ja talouden tiedekunta - Faculty of Management and Business
Hyväksymispäivämäärä
2025-05-28
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202505276283
https://urn.fi/URN:NBN:fi:tuni-202505276283
Tiivistelmä
In an era of accelerating digital transformation, research and development (R&D) organisations should adopt emerging office technologies that boost collaboration and raise efficiency. This single-case, mixed-methods study investigates two such tools—Microsoft Loop and Copi-lot—within the Finnish R&D unit of material handling solutions provider Konecranes. Guided by workflow efficiency literature, the Technology Acceptance Model (TAM), the Technology–Organisation–Environment (TOE) framework and organisational-inertia theory, the study ad-dressed two research questions: (1) How do employees understand workflow efficiency in an R&D organization? and (2) In what ways does the adoption of digital office technologies impact workflow efficiency?
To answer the research questions, a sequential mixed-methods design was employed. Eight interviews first identified workflow pain points, informing a baseline survey (n = 30) that assessed the perceived importance of ten efficiency factors. Following this, Microsoft Loop and Copilot were piloted within the organization. A follow-up survey measured their perceived impact, and nine interviews provided qualitative explanations for the results. Survey data were analyzed using descriptive statistics and correlations in Minitab; interviews were thematically coded in NVivo; and a Python-generated heat map showed the alignment between employee priorities and tool impacts.
As a result of the empirical investigation, several patterns emerged. Employees ranked Quality and Simplicity as the most critical workflow efficiency factors, followed by Human-Resource Utilization, Automation, Standardization, Flexibility, and Time. In assessing the tools’ impacts, Loop and Copilot delivered moderate-to-high positive effects across all dimensions (mean scores > +1 on a –3 to +3 scale), but in complementary ways: Copilot excelled in Automation, Time-savings, Human-Resource Utilization, and Quality, whereas Loop showed its greatest strengths in Simplicity, Time, and Standardization. Differences emerged by seniority and tenure: Senior employees prioritized Quality and Automation, focusing on strategic outcomes, while operational staff placed greater importance on Simplicity and Flexibility to ease day-to-day work demands. Also, longer-tenured employees showed a declining emphasis on Quality improvements, which may suggest a gradual adaptation and normalization of existing workflows. Finally, when examining technology adoption drivers and barriers, perceived usefulness, peer demonstrations, and managerial encouragement emerged as key enablers. However, adoption was hindered by behavioral inertia and integration limitations with Jira, an internal project management system.
While offering valuable insights, the study is limited by its single-case design, short piloting period, and focus on one organizational context, limiting generalizability. Future longitudinal, multi-industry research is recommended to validate and extend findings.
Overall, Copilot (strongest in automation, quality, HRU, time-savings) and Loop (strongest in simplicity, time, standardization) can meaningfully enhance workflow efficiency when solving clear pain points, integrating with core systems, and gaining managerial and peer support. Organisations should stage roll-outs around role-specific priorities, pair AI output with human re-view, and combine standard templates with local flexibility in Loop, supported by micro-training and internal success stories. Academically, the study extends TAM-TOE-inertia work by showing how seniority, tenure and peer influence shape technology uptake, and it introduces a heat-map method for testing problem–solution fit. Future research should link subjective perceptions with objective productivity and cost metrics, explore deeper Loop/Copilot integrations (e.g., Jira, PLM), and examine how employee backgrounds influence adoption patterns.
To answer the research questions, a sequential mixed-methods design was employed. Eight interviews first identified workflow pain points, informing a baseline survey (n = 30) that assessed the perceived importance of ten efficiency factors. Following this, Microsoft Loop and Copilot were piloted within the organization. A follow-up survey measured their perceived impact, and nine interviews provided qualitative explanations for the results. Survey data were analyzed using descriptive statistics and correlations in Minitab; interviews were thematically coded in NVivo; and a Python-generated heat map showed the alignment between employee priorities and tool impacts.
As a result of the empirical investigation, several patterns emerged. Employees ranked Quality and Simplicity as the most critical workflow efficiency factors, followed by Human-Resource Utilization, Automation, Standardization, Flexibility, and Time. In assessing the tools’ impacts, Loop and Copilot delivered moderate-to-high positive effects across all dimensions (mean scores > +1 on a –3 to +3 scale), but in complementary ways: Copilot excelled in Automation, Time-savings, Human-Resource Utilization, and Quality, whereas Loop showed its greatest strengths in Simplicity, Time, and Standardization. Differences emerged by seniority and tenure: Senior employees prioritized Quality and Automation, focusing on strategic outcomes, while operational staff placed greater importance on Simplicity and Flexibility to ease day-to-day work demands. Also, longer-tenured employees showed a declining emphasis on Quality improvements, which may suggest a gradual adaptation and normalization of existing workflows. Finally, when examining technology adoption drivers and barriers, perceived usefulness, peer demonstrations, and managerial encouragement emerged as key enablers. However, adoption was hindered by behavioral inertia and integration limitations with Jira, an internal project management system.
While offering valuable insights, the study is limited by its single-case design, short piloting period, and focus on one organizational context, limiting generalizability. Future longitudinal, multi-industry research is recommended to validate and extend findings.
Overall, Copilot (strongest in automation, quality, HRU, time-savings) and Loop (strongest in simplicity, time, standardization) can meaningfully enhance workflow efficiency when solving clear pain points, integrating with core systems, and gaining managerial and peer support. Organisations should stage roll-outs around role-specific priorities, pair AI output with human re-view, and combine standard templates with local flexibility in Loop, supported by micro-training and internal success stories. Academically, the study extends TAM-TOE-inertia work by showing how seniority, tenure and peer influence shape technology uptake, and it introduces a heat-map method for testing problem–solution fit. Future research should link subjective perceptions with objective productivity and cost metrics, explore deeper Loop/Copilot integrations (e.g., Jira, PLM), and examine how employee backgrounds influence adoption patterns.