Abstract
Every day employees learn about things happening in their company. This includes plain facts witnessed while on the job, related or not to one’s job responsibilities. Many of these facts, which we call “occurrence data”, are known by employees but remain unknown to the company. We suppose that some of them are valuable and may improve the company’s situational awareness. In the spirit of mobile crowdsensing, we propose intra-company crowdsensing (ICC), a method of “extracting” occurrence data from employees. In ICC, an employee occasionally responds to sensing requests, each about one plain fact. We elaborate the concept of ICC, proposing a model of human-system interaction, a system architecture, and an organizational process. We position ICC with respect to related concepts from information technology, and we look at it from selected organizational and managerial viewpoints. Finally, we conducted a survey, in which we presented the concept of ICC to employees of different companies and asked for their evaluation. Respondents positive about ICC outnumbered skeptics by a wide margin. The survey also revealed some concerns, mostly related to ICC being perceived as another employee surveillance tool. However, useful and acceptable sensing requests are likely to be found in every organization.
Highlights
Received: 6 November 2021Consider energy consumption in a typical office building
Responding to intra-company crowdsensing (ICC) sensing requests can be positioned within a HiTLCPS taxonomy [34] in two places: in sensing (“direct feeding the system with information”) and processing
experience sampling method (ESM) is more about experiences, while ICC is about plain facts
Summary
Rationale: employees know potentially useful facts that are overlooked. How INFOBot works:. If the respondent chooses “unlikely” or “very unlikely”, we ask for an explanation Hello, this is INFOBot. If possible, please tell me if you saw any unnecessarily lit halls when you arrived at work this morning. (i) yes, (ii) no, (iii) I don’t remember Hello, this is INFOBot. If possible, please tell me approximately how many times you have experienced paper jams in the departmental printer within the last thirty days. In the subsequent section (Table 2, items 9–13), we ask for a high-level evaluation of the INFOBot concept: how many sensing requests per time unit the respondent would be willing to receive, whether they would be open to having INFOBot in their company, and if INFOBot can have a negative impact on their comfort at work (and if so, in what way). In the last section of the questionnaire (Table 2, items 14–21), we ask for the respondent’s demographic data
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