The Role of Monthly Office Days in a Fully Remote Work Model

Remote work has become a central aspect of the modern work environment, driven by health concerns and technological advancements. The sudden transition to remote work during the pandemic offered a large-scale, real-time experiment on its impacts. While many employees have appreciated the flexibility, concerns about decreased productivity and diminished job satisfaction persist. Understanding how to optimise remote work arrangements is crucial for both employees’ well-being and organisational efficiency.
This study aims to fill this gap by investigating whether incorporating monthly office visits into a fully remote work model improves productivity and job satisfaction among call center agents in Şanlıurfa, Turkey. By employing a randomised control trial, the study will compare a treatment group with monthly office visits to a control group that remains fully remote. Key variables include productivity metrics, job satisfaction scores, and retention rates, measured over a nine-month period with follow-up surveys for long-term effects. The findings aim to inform organizational policies, enhancing both employee satisfaction and productivity in remote and hybrid work settings.

The student’s tasks will include:

• Contributing to the preparation of research reports and policy briefs summarizing key findings.
• Assisting in data collection and organization, including productivity metrics, survey responses, and retention rates.
• Conducting preliminary data analysis using econometric methods.
• Supporting the implementation of follow-up surveys to assess long-term impacts.

• The student will gain direct exposure to an active randomized control trial (RCT) in a real-world setting, contributing to cutting-edge research on remote and hybrid work models.
• The student will develop quantitative analysis skills, including handling large datasets, applying econometric techniques, and working with productivity and survey data.
• The student will deepen their understanding of experimental research methods, including treatment assignment, control groups, and difference-in-differences estimation.
• By engaging with research on workplace productivity and job satisfaction, the student will gain insights into labor economics and organizational behavior, particularly relevant for policymakers and businesses designing hybrid work policies.
• The student will have the opportunity to work alongside researchers from top institutions (EBRD, King’s College London, Stanford University, Paris School of Economics), providing exposure to high- level academic and policy-oriented research.
• The internship will enhance the student’s problem-solving, critical thinking, and communication skills, which are valuable for future roles in academia, consulting, or policy-making.
• Strong performance during the internship may lead to opportunities for co-authorship, further research collaborations, or policy consulting roles.

• Candidates should be proficient in Stata or R and familiar with advanced causal inference techniques.
• A solid understanding of econometric methods is essential, including difference-in-differences (DiD), fixed effects models. Experience working with experimental and quasi-experimental research designs is highly desirable.
• The student should be skilled in cleaning, organizing, and processing datasets, ensuring data integrity and reproducibility.

• The student will prepare a summary report detailing key findings, methodologies, and insights gained during The internship.
• If applicable, they may present their work at academic seminars, workshops, or conferences related to labor economics, remote work, or policy evaluation.
• The student may share their experience through a presentation or seminar at their university, discussing The research process, key takeaways, and policy implication.

1. Please send your CV and a brief cover letter outlining your interest and suitability to the project supervisor(s). Please contact the project supervisor(s) in advance of submitting the application with any questions.

2. If selected by the project supervisor:

• LISS DTP students must then complete the LISS DTP Placement /Internship Application form. This ensures that there is approval of PhD supervisor, and the necessary information is obtained to extend funding (for DTP1 students) or confirm placement requirement fulfilled (for DTP2 students), and to fulfil ESRC reporting obligations. LISS DTP approval must be given before the RA internship can commence.
• Other ESRC-funded DTP students should follow the internship application processes from their home DTP.

Please note for LISS DTP students:

• Research Assistant Internships must not be undertaken with the student’s current supervisor and/or home department.
• DTP1 students (those whose funding commenced before Oct24): a maximum of 4 Research Assistant internships will be funded. These will be filled on a first-come, first-served basis. Once the 4 DTP1 places are filled, we will inform PIs that only DTP2 students are eligible for the Research Assistant internships. PLEASE NOTE THAT ALL DTP1 PLACES HAVE NOW BEEN FILLED.
• DTP2 students (those whose funding commenced from Oct24): are required to complete a 3-month placement, which is funded through their studentship. No limits to number that can be funded.
• Reports: at the conclusion of the internship, the student will be required to complete an internship report, which will include a question for the internship host to feedback on the internship.

Contact liss-dtp@kcl.ac.uk with any questions.