4
Innovation Attributes in MCDA
The mining industry continually seeks to enhance its prac-
tices through research and development initiatives (Nieto,
2023). However, the selection of R&D projects demands
a systematic approach that considers innovation attri-
butes beyond economic and production factors. It is, thus,
imperative that every project being considered brings an
innovation attribution into any decision-making process
including MCDA.
By employing MCDA, mining companies and manag-
ers can effectively analyze and prioritize projects based on
a comprehensive assessment of their potential benefits and
drawbacks across multiple dimensions, facilitating more
informed and robust decision-making processes.
As mentioned by Nieto (2019), selecting research and
development (R&D) projects in mining requires a careful
evaluation of various innovation attributes beyond eco-
nomic and operational considerations.
By adopting MCDA, mining companies can assess
R&D projects based on their innovation attributes holisti-
cally. This enables a comprehensive understanding of the
potential technology driven benefits and drawbacks associ-
ated with each project, facilitating a more informed selec-
tion process. (Nieto, 2023)
Any mining industry considering an innovation trans-
formation process will end up facing some aspects of the
five innovation technology drivers as described by Nieto,
(2023): Safety, Simplification, Smart, Stealth-footprint and
Sustainability resulting in a modern technology sustainable
mining operation.
Safety Technology
Safety is paramount in the mining industry. R&D proj-
ects that focus on improving safety measures and reducing
hazards should be assigned significant importance. MCDA
allows decision- makers to quantify the safety benefits of a
project and incorporate them into the overall evaluation.
Simplification of Systems
Complex mining systems can lead to inefficiencies and
increased risks. R&D projects aiming to simplify processes
and systems should be considered favorably. MCDA assists
in assessing the potential impact of system simplification,
enabling informed decisions.
Smart-Digital Technology
Integrating smart and digital technologies can enhance
mining operations, increasing efficiency, and reducing costs.
MCDA facilitates the evaluation of the benefits associated
with implementing such technologies, considering factors
like automation, data analytics, and real- time monitoring.
Stealth/Footprint Minimization Technology
Reducing the environmental footprint of mining activities
is crucial for sustainable operations. R&D projects that
focus on minimizing the environmental impact should
be evaluated using MCDA, considering factors such as
waste reduction, energy efficiency, and responsible resource
extraction.
Sustainable Technology
Mining projects that embrace environmentally sustain-
able technologies contribute to long-term viability. MCDA
enables decision-makers to quantify the environmental
benefits of a project, considering attributes like renew-
able energy integration, water management, and land
rehabilitation.
Assign Weights to Each Attribute Based on Their
Relative Importance or Priority
Table 1 shows examples of the proposed attributes for each
of the categories being considered.
The weights should reflect the company’s preferences
and priorities indicating the company’s qualitative or quan-
titative value. Weights can be determined through various
methods, such as direct rating, pairwise comparison, or
analytic hierarchy process (AHP) briefly described below.
Direct Rating
Direct Rating is a simple method where managers or deci-
sion-makers assign numerical ratings or scores to each alter-
native project based on predetermined criteria or attributes.
Nedashkovskaya (2022). The decision-makers directly rate
each project independently, typically using a numerical
scale. The ratings can be based on subjective judgment
or objective measures. Once the ratings are assigned, the
weights of the projects are determined based on the assigned
scores.
Pairwise Comparison
Pairwise Comparison is a method that involves comparing
each alternative project or attribute with every other project
or attribute in pairs to determine their relative importance
or priority. Nedashkovskaya, (2022).
Decision-makers evaluate the projects and attributes
based on a specific criterion and indicate which project
they consider to be more favorable or superior. This process
is repeated for all possible pairs of projects and attributes,
Innovation Attributes in MCDA
The mining industry continually seeks to enhance its prac-
tices through research and development initiatives (Nieto,
2023). However, the selection of R&D projects demands
a systematic approach that considers innovation attri-
butes beyond economic and production factors. It is, thus,
imperative that every project being considered brings an
innovation attribution into any decision-making process
including MCDA.
By employing MCDA, mining companies and manag-
ers can effectively analyze and prioritize projects based on
a comprehensive assessment of their potential benefits and
drawbacks across multiple dimensions, facilitating more
informed and robust decision-making processes.
As mentioned by Nieto (2019), selecting research and
development (R&D) projects in mining requires a careful
evaluation of various innovation attributes beyond eco-
nomic and operational considerations.
By adopting MCDA, mining companies can assess
R&D projects based on their innovation attributes holisti-
cally. This enables a comprehensive understanding of the
potential technology driven benefits and drawbacks associ-
ated with each project, facilitating a more informed selec-
tion process. (Nieto, 2023)
Any mining industry considering an innovation trans-
formation process will end up facing some aspects of the
five innovation technology drivers as described by Nieto,
(2023): Safety, Simplification, Smart, Stealth-footprint and
Sustainability resulting in a modern technology sustainable
mining operation.
Safety Technology
Safety is paramount in the mining industry. R&D proj-
ects that focus on improving safety measures and reducing
hazards should be assigned significant importance. MCDA
allows decision- makers to quantify the safety benefits of a
project and incorporate them into the overall evaluation.
Simplification of Systems
Complex mining systems can lead to inefficiencies and
increased risks. R&D projects aiming to simplify processes
and systems should be considered favorably. MCDA assists
in assessing the potential impact of system simplification,
enabling informed decisions.
Smart-Digital Technology
Integrating smart and digital technologies can enhance
mining operations, increasing efficiency, and reducing costs.
MCDA facilitates the evaluation of the benefits associated
with implementing such technologies, considering factors
like automation, data analytics, and real- time monitoring.
Stealth/Footprint Minimization Technology
Reducing the environmental footprint of mining activities
is crucial for sustainable operations. R&D projects that
focus on minimizing the environmental impact should
be evaluated using MCDA, considering factors such as
waste reduction, energy efficiency, and responsible resource
extraction.
Sustainable Technology
Mining projects that embrace environmentally sustain-
able technologies contribute to long-term viability. MCDA
enables decision-makers to quantify the environmental
benefits of a project, considering attributes like renew-
able energy integration, water management, and land
rehabilitation.
Assign Weights to Each Attribute Based on Their
Relative Importance or Priority
Table 1 shows examples of the proposed attributes for each
of the categories being considered.
The weights should reflect the company’s preferences
and priorities indicating the company’s qualitative or quan-
titative value. Weights can be determined through various
methods, such as direct rating, pairwise comparison, or
analytic hierarchy process (AHP) briefly described below.
Direct Rating
Direct Rating is a simple method where managers or deci-
sion-makers assign numerical ratings or scores to each alter-
native project based on predetermined criteria or attributes.
Nedashkovskaya (2022). The decision-makers directly rate
each project independently, typically using a numerical
scale. The ratings can be based on subjective judgment
or objective measures. Once the ratings are assigned, the
weights of the projects are determined based on the assigned
scores.
Pairwise Comparison
Pairwise Comparison is a method that involves comparing
each alternative project or attribute with every other project
or attribute in pairs to determine their relative importance
or priority. Nedashkovskaya, (2022).
Decision-makers evaluate the projects and attributes
based on a specific criterion and indicate which project
they consider to be more favorable or superior. This process
is repeated for all possible pairs of projects and attributes,