[论文解读] How does Working from Home Affect Developer Productivity? -- A Case Study of Baidu During COVID-19 Pandemic

Lingfeng Bao, Tao Li+4 more|arXiv (Cornell University)|May 27, 2020

Technology Adoption and User Behaviour被引用 29

一句话总结

本研究利用新冠疫情爆发期间139名百度开发人员在138个工作日内的每日活动日志，定量分析了居家办公（WFH）对软件开发人员生产力的影响。研究发现，WFH的影响具有混合性——在代码审查等指标上呈正面影响，而在提交代码和构建次数等指标上则呈负面影响，具体影响取决于项目特征和个体开发人员的行为。

ABSTRACT

Nowadays, working from home (WFH) has become a popular work arrangement due to its many potential benefits for both companies and employees (e.g., increasing job satisfaction and retention of employees). Many previous studies have investigated the impact of working from home on the productivity of employees. However, most of these studies usually use a qualitative analysis method such as survey and interview, and the studied participants do not work from home for a long continuing time. Due to the outbreak of coronavirus disease 2019 (COVID-19), a large number of companies asked their employees to work from home, which provides us an opportunity to investigate whether working from home affects their productivity. In this study, to investigate the difference of developer productivity between working from home and working onsite, we conduct a quantitative analysis based on a dataset of developers' daily activities from Baidu Inc, one of the largest IT companies in China. In total, we collected approximately four thousand records of 139 developers' activities of 138 working days. Out of these records, 1,103 records are submitted when developers work from home due to COVID-19 pandemic. We find that WFH has both positive and negative impacts on developer productivity in terms of different metrics, e.g., the number of builds/commits/code reviews. We also notice that working from home has different impacts on projects with different characteristics including programming language, project type/age/size. For example, working from home has a negative impact on developer productivity for large projects. Additionally, we find that productivity varies for different developers. Based on these findings, we get some feedbacks from developers of Baidu and understand some reasons why WFH has different impacts on developer productivity.

研究动机与目标

• 利用真实世界活动数据，研究居家办公对软件开发人员长期生产力的影响。
• 识别项目特定因素（如规模、年龄、类型和编程语言）如何调节WFH对生产力的影响。
• 理解在远程工作条件下个体生产力的差异。
• 为公司和开发人员提供数据驱动的远程软件开发管理建议。

提出的方法

• 收集并分析了139名百度开发人员在138个工作日内的每日软件开发活动日志（如提交、构建、代码审查）。
• 对比了疫情期间居家办公（WFH）与现场办公条件下的生产力指标。
• 使用统计分析方法，比较不同工作模式下生产力指标（均值、中位数）的聚合结果。
• 研究了项目层面特征（如编程语言、项目类型、规模和年龄）对生产力结果的影响。
• 通过与百度开发人员进行定性反馈访谈，解释定量研究结果并识别潜在的行为因素。
• 采用混合方法研究，结合定量指标与开发人员反馈，解释生产力趋势的差异。

实验结果

研究问题

• RQ1 居家办公如何影响不同软件开发指标（如提交、构建和代码审查）下的开发人员生产力？
• RQ2 项目层面的特征（如规模、年龄、类型、编程语言）如何调节远程工作对开发人员生产力的影响？
• RQ3 开发人员之间的个体差异在多大程度上影响其居家办公时的生产力？
• RQ4 在远程工作条件下，观察到的生产力差异背后 perceived 的原因是什么？

主要发现

• 居家办公对每日完成的代码审查数量有正面影响，表明远程环境下协作或审查效率有所提升。
• WFH导致提交次数和构建次数显著减少，表明在某些开发工作流中产出或任务完成度下降。
• 在大型项目中，居家办公对开发人员生产力产生了显著的负面影响，可能源于协调开销增加。
• 个体开发人员之间的生产力差异显著，部分人在远程工作时产出增加，而另一些人则出现下降。
• WFH的影响在使用特定编程语言的项目中更为显著，但结果中未对具体语言效应进行量化。
• 开发人员反馈表明，沟通障碍和非正式互动减少是远程环境下生产力下降的主要原因。