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Table 7 Construct and indicator items with the supporting research

From: Big data analytics: a link between knowledge management capabilities and superior cyber protection

 

Construct and indicator items

Supporting research

 

KM acquisition process

 

ACQ1

Has processes for acquiring knowledge about our customers.

Gold, Malhotra & Segars, 2001

ACQ2

Has processes for acquiring knowledge about our suppliers.

Gold, Malhotra & Segars, 2002

ACQ3

Has processes for exchanging knowledge with our business partners.

Gold, Malhotra & Segars, 2004

ACQ4

Has processes for acquiring knowledge about competitors within our industry

Gold, Malhotra & Segars, 2006

 

KM conversion

 

COV1

Has processes for converting knowledge into the design of new products and services

Gold, Malhotra & Segars, 2011

COV2

Has processes for converting competitive intelligence into plans of action

Gold, Malhotra & Segars, 2012

COV3

Has processes for transferring organizational knowledge to individuals.

Gold, Malhotra & Segars, 2014

COV4

Has processes for absorbing knowledge from business partners into the organization

Gold, Malhotra & Segars, 2016

COV5

Has processes for distributing knowledge throughout the organization.

Gold, Malhotra & Segars, 2017

 

KM application

 

APP1

Has processes for using knowledge in development of new products/service

Gold, Malhotra & Segars, 2022

APP2

Has processes for using knowledge to solve new problems.

Gold, Malhotra & Segars, 2023

APP3

Uses knowledge to adjust strategic direction.

Gold, Malhotra & Segars, 2025

APP4

Is able to locate and apply knowledge to changing competitive condition

Gold, Malhotra & Segars, 2026

APP5

Makes knowledge accessible to those who need it.

Gold, Malhotra & Segars, 2027

APP6

Quickly applies knowledge to critical competitive needs.

Gold, Malhotra & Segars, 2029

 

Pre-cyber incidence agility

 

PRC1

We identify and detect cyber anomalies faster than previous

 

PRC2

The speed of identifying cyber threats has improved

 

PRC3

We identify vulnerabilities faster

 

PRC4

We are able to respond faster to changing threat landscape

 
 

Post-cyber incidence Agility

 

POC1

Our speed of responding to potential threat has increased

 

POC2

Our incidence recovery rate has improved

 

POC3

The time to recover from an incidence has gone down

 
 

Improved cyber incidence detection and resolution

 

CID1

We have reduced the amount of time to collect and analyze data that are relevant to investigations

 

CID2

We have reduced amount of time it takes to resolve cyber incidences

 

CID3

We have reduced risk of cybertheft by reducing the number of false positives

 

CID4

Our threat detection rate has gone up

 
 

Reduced business impacts

 

RBI1

Cyber Incidences has less impacts on our productivity

 

RBI2

Financial loss from cyber incidence has reduced considerably

 

RBI3

Risk to theft of intellectual property by cyber criminals have dropped

 

RBI4

Overall the business impacts of breaches have reduced significantly

 
 

Big Data Analytics Adoption measurements

 

BDA1

We have access to very large, unstructured, or fast-moving data for analysis

Davenport (2014)

BDA2

We integrate data from multiple internal sources into a data warehouse or mart for easy access

Davenport (2014)

BDA3

We have explored or adopted parallel computing approaches (e.g. Hadoop) to big data processing

Davenport (2014)

BDA4

We have explored or adopted different data visualization tools

Davenport (2014)

BDA5

We have explored or adopted new forms of databases such as Not Only SQL (NoSQL) for storing data

Gordon (2007)

BDA6

We have explored or adopted open source software for big data analytics

Davenport (2014)