Online social transparency in enterprise information systems: a risk assessment method

Abstract

Teleworking refers to the utilization of information and communication technologies for work done outside the workplace. The Covid-19 crisis led to increased utilisation of social networking tools within enterprises, especially when working remotely. The aim of their use is often to improve situational awareness, coordination, and collaboration amongst employees. Online social transparency, typically done through social networks or enterprise social software, refers to the voluntary sharing of personal and contextual information such as those relating to their own and team status, intentions, motivation, capabilities, goal priorities besides updates on the physical and social context, with other colleagues. An ad-hoc practice of social transparency can introduce risks such as information overload, social loafing and peer pressure. Despite recognising its adverse effects, there is a lack of systematic methods that identify and assess the risks of online social transparency. In this paper, we present a method to identify and evaluate these within enterprises. We present the method’s workflow, stakeholders, the novel artefacts and techniques devised to use and the outcomes to produce. We evaluate our proposed method by applying it in a real organisational context and assess applicability, efficiency, and effectiveness in identifying risks and supporting managers in risk assessment. The results showed that the method gives a framework of thinking and analysis and helps recognize and identify risks in a specialized manner.

Enhancing students’ online collaborative PBL learning performance in the context of coauthoring-based technologies: A case of wiki technologies

“…Drawing upon the theoretical perspective of social identity and social capital, this study describes why wikis’ completeness and understandability are associated with students’ trust (H1a, H2a) and social identity (H2b). These results are in line with those of previous studies (e.g., Alsaedi et al, 2022 ; Eldrandaly et al, 2022 ; Gong et al, 2007 ; Lee et al, 2019 ; Shahzad et al, 2020 ; Zavolokina et al, 2020 ). H1b is insignificant; thus, we examined the mediating effect of trust by using Hayes process macro techniques of bootstrapping with a 95% confidence interval (CI) with 5000 resamples (Hayes, 2012 ).…”

“…Additionally, when a platform (i.e., wikis) is easier to understand, this will determine the breadth of its application, making its content easier to (Etien et al, 2015). It can be inferred that understandability is also related to transparency (i.e., identification, content, interaction), allowing a quick understanding of the knowledge/information of this platform (Alsaedi et al, 2022;Eldrandaly et al, 2022). Furthermore, if a system is known, shaping a user's trust in the ecosystem service of this platform is more effortless.…”

“…Based on the end user's perception, the understandability of the learned information/knowledge enabled by Web 2.0 technologies (e.g., wikis) may be an important antecedent of perceived identification for the end user (Alsaedi et al, 2022). Some studies have stated that understandability is related to critical indicators of learning performance, including reasoning skills (vanOostveen et al, 2019;Zhu & Zhang, 2022), engagement/participation, and motivation (Zhang et al, 2021), and therefore can impact the effectiveness of collaborative learning efforts.…”