Knowledge sharing and protection in data-centric collaborations: An exploratory study

Total interpretive structural modelling (TISM) and MICMAC approach in analysing knowledge risks in ICT-supported collaborative project

Purpose

As emphasised by the theory of knowledge-based view, knowledge constitutes the basic element for a firm’s competitive advantage. Consequently, a firm’s knowledge at risk could have an adverse effect on its performance. In this regard, this paper aims to investigate potential knowledge risks present in an (ICT)-supported collaborative project and establishes inter- and multi-relationships among these risks.

Design/methodology/approach

In this paper, an integrated approach using the total interpretive structural modelling (TISM) technique and MICMAC analysis is implemented to determine the hierarchical inter-relationships among knowledge risks and classify them according to their driving and dependence power.

Findings

The result reveals seven knowledge risks. The analysis establishes cybercrime and espionage as high drivers of knowledge risks in an ICT-supported collaborative project. Further, a comprehensive model is developed showing the hierarchical structure and multi- and inter-relationships among the analysed risks.

Practical implications

From a practical viewpoint, the proposed model in this study will be of great importance to practitioners because it highlights the most prominent knowledge risks in an ICT-supported collaborative project. Additionally, it will provide a clue for effective knowledge risk management in a systematic approach.

Originality/value

To the best of the author’s knowledge, this is one of the first studies to use both the TISM technique and MICMAC analysis to identify and classify knowledge risks in an ICT-supported collaborative project.

Show Me What You Do and I Will Tell You Who You Are: A Cluster Typology of Supply Chain Risk Management in SMEs

Although research on risk management (RM) in small- and medium-sized enterprises (SMEs) in general and regarding supply chains (SCs) has increased recently, our understanding is still rather fragmented and underdeveloped. This refers particularly to new types of risks such as dynamic crises or emerging risks associated with digital transformation (DT). Therefore, the purpose of this exploratory paper is to investigate RM in SMEs in SCs. More precisely, the aim is to identify patterns that can be used to group SMEs according to their risk behavior (i.e., risk attitude and perception). Drawing from a data set of 181 European SMEs, this paper empirically conceptualizes a typology of SMEs. The typology consists of four distinct types of SMEs that emerged from a cluster analysis: collective risk eliminators, collective playing it safe seekers, collective risk-ignoring knights of fortune, and collective neglecting imperturbable ones. The findings indicate that different risk behavior leads to different degrees of collaboration within the SC. Furthermore, the close interconnection between RM as found in the different clusters and the respective firm’s innovation performance can be shown. By acknowledging the heterogeneity found in SMEs, this paper breaks away from mainstream research that tends to consider SMEs as a homogeneous entity.