From broken habits to new intentions: how COVID-19 expands our knowledge on post-adoptive use behaviour of digital communication and collaboration

Figures & data

Figure 1. Organisational use of the four features over time.

Table 1. Descriptive statistics of MS teams feature use (rounded, per 30-day period).

	Chat				Meeting				Call				Channel
	T1	T2	T3	T4	T1	T2	T3	T4	T1	T2	T3	T4	T1	T2	T3	T4
Mean	85	120	193	350	3	5	10	31	1	2	3	12	2	4	3	5
Median	24	51	89	160	1	4	6	25	1	1	2	6	0	1	0	0
SD	142	140	249	464	3	5	10	25	2	3	5	15	5	9	6	13
Max	926	801	1990	3162	16	25	63	123	8	12	22	90	31	77	33	119

Table 2. Normalised clustering results (largest cluster size across all time periods in bold).

Cluster	Description	T	Chat	Meeting	Call	Channel	Size
C0	Largely passive or little use	1	.06	.12	.05	.01	29
		2	.06	.13	.04	.00	17
		3	.16	.17	.04	.00	15
		4	.13	.29	.03	.00	18
C1	Occasional use, primarily of Chat	1	.50	.00	.05	.06	18
		2	.64	.00	.20	.13	11
		3	.67	.06	.26	.27	10
		4	.32	.14	.43	.16	5
C2	Use of Chat and Meeting	1	.60	.56	.08	.13	25
		2	.59	.60	.05	.17	31
		3	.63	.62	.14	.02	35
		4	.60	.71	.21	.04	41
C3	Use of all features but Channel	1	.70	.65	.61	.13	46
		2	.79	.69	.60	.15	54
		3	.82	.79	.80	.11	54
		4	.82	.82	.72	.11	74
C4	Use of all features	1	.86	.79	.69	.71	40
		2	.86	.77	.63	.73	61
		3	.82	.72	.51	.73	67
		4	.85	.83	.67	.72	43

Table 3. Percentage of users in clusters for each hierarchical position and period.

C	Part-time Employee				Administrative Employee				Operational Employee
	T1	T2	T3	T4	T1	T2	T3	T4	T1	T2	T3	T4
0	19%	7%	8%	13%	86%	86%	86%	43%	7%	-	-	2%
1	20%	11%	10%	3%	-	-	-	29%	2%	-	-	-
2	19%	22%	24%	28%	-	-	-	14%	14%	16%	13%	9%
3	21%	25%	30%	33%	14%	-	-	-	48%	41%	38%	60%
4	21%	34%	28%	20%	-	14%	14%	14%	29%	43%	49%	30%
N	Large (>75)				Small (<15)				Medium (40–60)
C	Assistant to Head of Dept.				Head of Support Function				Head of Department
-	T1	T2	T3	T4	T1	T2	T3	T4	T1	T2	T3	T4
0	-	-	-	-	-	-	-	-	44%	44%	22%	11%
1	-	-	-	-	-	-	-	-	-	-	-	-
2	11%	11%	-	-	33%	-	-	-	-	11%	44%	67%
3	44%	89%	22%	67%	-	-	17%	50%	33%	33%	11%	11%
4	44%	-	78%	33%	67%	100%	83%	50%	22%	11%	22%	11%
N	Small (<15)				Small (<15)				Small (<15)

Table 4. Factors that contributed to individual sensemaking during COVID-19.

Resource Types	Contributing Factors	Changes with Social Distancing Measures due to COVID-19	Example Quote
Organisational Resources	Resource-Facilitating Conditions	Organisational investment in proactive technical support	“I have the incredible luxury of having the IT department at my side, explaining it to me and setting it up over hours”.
	Technology-Facilitating Conditions	Organisational investment in digital infrastructure	“Because we have no microphone and no headset here at work, and we were the last to be upgraded to Windows 10”.
	Available Technology	Already high maturity of communication and collaboration technology before the pandemic	“Only after we were able to change team Channel privacy, we started to use this functionality”.
	WFH-Policies and Recommendations	Recommendation for digital tools to maintain communication; all organisational meetings, such as jour fixes, pushed to MS Teams	“We were encouraged to do more things via MS Teams. For example, with mentoring, the organisational recommendation was to do it via teams rather than not do it at all”.
Network Resources	Team Norms	Team efforts to find new norms for remote work	“Answering questions via chat does not work for us because we work as a team. We can access each other’s e-mails, but not the chat – so it would not be documented and retraceable what happened”.
	Superior Influence	Maintaining close contact with superiors had to go through digital communication	“My boss did not like to communicate via WhatsApp. Therefore, we quickly moved our communication to MS Teams”.
	Peer Influence	Peer group expands beyond geographically close contacts, shifts to others with similar tasks	“I was also in contact with [colleague from other location] via teams. It was great syncing with her: how are they doing it, how are we doing it”
	Network Externalities	Better reachability of colleagues increases network effects	“In the long run, MS Teams [Chat] has become more used by everyone and therefore, more useful”.
	Geographic Proximity	Increased work-from-home decreases proximity	“MS Teams meetings were used for all meetings where it was clear from the outset that they were not in the same location”.
Individual Resources	Technology Self-Efficacy	Necessary exposure to IT reinforces self-efficacy beliefs of individuals with low IT confidence	“For me, the first week with MS Teams was chaos, but that’s probably also due to my technical know-how. […] If you don’t have to deal with it, then you don’t do it. For us [older people], there is a greater entry barrier than for the young people”.
	Past Experiences	Previous experience working with individuals from other locations became valuable	“Which tool is ultimately used is based on habit. The Heads of Departments are used to simply writing e-mails”.
	Cognitive Capacity	Increased digital communication within the organisation leads to a higher cognitive load	“My attention is on e-mails, chat and calls – it’s not possible for me to follow the team’s channels in parallel as well. That’s too many channels. When the team actively needs me, they write e-mails or chat messages”.

Figure 2. Hybrid model of sensemaking and post-adoptive communication and collaboration use.

Figure 3. Hybrid model of teams use exemplarily instantiated based on data of head of support function 2.