Responsible consumption and production (RCP) in corporate decision-making models using soft computation
| Published date | 12 March 2018 |
| Date | 12 March 2018 |
| DOI | https://doi.org/10.1108/IMDS-11-2017-0507 |
| Pages | 322-329 |
| Author | Ming-Lang Tseng,Qinghua Zhu,Joseph Sarkis,Anthony S.F. Chiu |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
Guest editorial
Responsible consumption and production (RCP) in corporate decision-making
models using soft computation
Introduction
RCP is critical to a sustainable world. Human and environmental systems interact through
the economic system in various ways that have caused many unsustainable issues to arise.
Solving these problems is a non-trivial exercise and could be considered one of the world’s
“wicked”problems (Churchman, 1967). Wicked problems are complex, intractable,
conflicting, and multidimensional problems many times with unforeseen and unintended
consequences. It is within this context that the use of soft computation may be a valuable set
of tools to handle wicked problems from an RCP perspective.
The United Nations’Sustainable Development Goals (SDGs) have been developed to set
an agenda to transform nations, businesses, and society to become more sustainable by
2030 (Griggs et al., 2013). In total, 17 goals were set in various social, economic, and
environmental issues. SDG 12 titled, “Responsible consumption and production,”has a
long history in various international conferences and actions. RCP is meant to ensure
sustainable consumption and production (SCP) patterns. This SDG sets the stage by
stating that a strong national framework for Achieving Goal 12 requires a strong national
framework for SCP be integrated into regulatory plans and policies, business practices
and consumer behavior, together while adhering to international norms on hazardous
chemicals and waste management (United Nations Development Programme (UNDP), 2016).
Essentially, the goal here is focusing on various elements of the supply chain ranging
from deep in the supply chain and extractive industries, to individual consumer needs.
Green supply chains and green consumerism are evident in many of the considerations
and research streams necessary to more fully understand how progress can be made
on SDG 12.
RCP in business usually contains the qualitative and quantitative information as well as
complex phenomena for decision-making processes (Roy and Singh, 2017). In this context,
soft computing attempts to study, model, and analyze complex situations for which
conventional methods, such as single criteria financial measures such as return on
investment or payback, have not yielded complete solutions to these complex and strategic
problems (Presley et al., 2016). This special issue (SI) exploits SCP in corporate
decision-making models’tolerance for imprecision, uncertainty, and partial truth to achieve
tractability, robustness, and better rapport with reality. Applying soft computing can
potentially eliminate noise to ensure SCP development. Soft computing can have a variety of
definitions, but a common theme is to taking into consideration the human mind,
imprecision, and differing behavioral issues that are not considered in “hard computing”
optimization approaches (Zadeh, 1997; Magdalena, 2010). Hence, there is a need to
further explore how soft computing is positioned, conceptualized, and applied in current
RCP developments.
Viewpoints and tools from management science, operations research, economics,
engineering, and other relevant domains are needed. These multiple disciplines exemplify
the need for interdisciplinary and transdisciplinary research to investigate SCP topics
(Schaltegger et al., 2013). Transdisciplinary research goes beyond the traditional academic
disciplines suchas basic sciences as chemistry and social sciences as management science to
incorporatepolicy makers, industrial practitioners, and evenconsumers (Sahamie et al., 2013).
This environment sets the stage for some aspects of soft computing that can integrate
Industrial Management & Data
Systems
Vol. 118 No. 2, 2018
pp. 322-329
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-11-2017-0507
322
IMDS
118,2
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