CHINESE ROAD TO RESPONSIBLE INNOVATION: CONSTRUCTING A GREEN PORT IN DALIAN

Bottom of the Pyramid (BoP) organizations are the ones that develop a set of capabilities that contribute to create short- and long-term sustainability values inside and outside the boundaries of BoP ecosystems. Capabilities have an important role in BoP organizations’ strategies that aim to solve BoP issues. Notwithstanding its developments, BoP research still lacks theoretical contributions for the analysis of organizations. We suggest special attention to the need of advancing knowledge on capabilities of BoP organizations because this field is scattered and fragmented, misinterpreted, and still underdeveloped in the literature. We oriented our research formulating and seeking answers to our main question on what are the capabilities needed to enable organizations to create sustainability values in BoP ecosystems? We conducted an integrative review of BoP research for the period from 1998 to 2019, and we found 22 key capabilities of BoP organizations. We organized the capabilities into four major categories including BoP Responsible Consumption, BoP Responsible Business Model, BoP Responsible Management, and BoP Responsible Innovation. We advanced propositions and discussions regarding the capabilities and major categories’ popularity, interdependence and combination, short- and long-term temporal functions, sustainability roles, and effectiveness to address BoP issues. Our article organizes the field of capabilities of BoP organizations; advances contributions and implications for management, organizations, and policymaking; and opens fruitful avenues for future research.

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Responsible innovation, anticipation and responsiveness: case studies of algorithms in decision support in justice and security, and an exploration of potential, unintended, undesirable, higher-order effects

AI and Ethics ◽

10.1007/s43681-021-00063-2 ◽

2021 ◽

Author(s):

Marc Steen ◽

Tjerk Timan ◽

Ibo van de Poel

Keyword(s):

Decision Support ◽

Case Studies ◽

Personal Data ◽

Higher Order ◽

Popular Media ◽

Responsible Innovation ◽

Order Effects ◽

Key Dimensions ◽

Higher Order Effects

AbstractThe collection and use of personal data on citizens in the design and deployment of algorithms in the domain of justice and security is a sensitive topic. Values like fairness, autonomy, privacy, accuracy, transparency and property are at stake. Negative examples of algorithms that propagate or exacerbate biases, inequalities or injustices have received ample attention, both in academia and in popular media. To supplement this view, we will discuss two positive examples of Responsible Innovation (RI): the design and deployment of algorithms in decision support, with good intentions and careful approaches. We then explore potential, unintended, undesirable, higher-order effects of algorithms—effects that may occur despite good intentions and careful approaches. We do that by engaging with anticipation and responsiveness, two key dimensions of Responsible Innovation. We close the paper with proposing a framework and a series of tentative recommendations to promote anticipation and responsiveness in the design and deployment of algorithms in decision support in the domain of justice and security.

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Analysing acceptability of E-rickshaw as a public transport innovation in Delhi: A responsible innovation perspective

Technological Forecasting and Social Change ◽

10.1016/j.techfore.2021.120908 ◽

2021 ◽

Vol 170 ◽

pp. 120908

Author(s):

Dr Rajbeer Singh ◽

Shilpa Mishra ◽

Krishna Tripathi

Keyword(s):

Public Transport ◽

Responsible Innovation

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Selecting Suitable, Green Port Crane Equipment for International Commercial Ports

Sustainability ◽

10.3390/su13126801 ◽

2021 ◽

Vol 13 (12) ◽

pp. 6801

Author(s):

Guo-Ya Gan ◽

Hsuan-Shih Lee ◽

Yu-Jwo Tao ◽

Chang-Shu Tu

Keyword(s):

Data Envelopment Analysis ◽

Environmental Protection ◽

Green Energy ◽

Programming Approach ◽

Data Envelopment ◽

Container Handling ◽

Dea Method ◽

Green Port ◽

Large Container ◽

Gantry Cranes

Responding to the increasing global need for environmental protection, a green port balances economic vibrancy with environmental protection. However, because exhaust emissions (e.g., CO2 or sulfide) are difficult to monitor around ports, data on such emissions are often incomplete, which hinders research on this topic. The present study aimed to fill this gap in this topic. To remedy this problem, this study formulated a new data envelopment analysis (DEA) method for collecting CO2 emissions data at their source. This method was applied to collect real-world operating data from a large container-handling company in Taiwan. Specifically, we provide a real example using a novel green energy index to account for undesirable outputs. Our main objective was to formulate two methods that combine: (1) data envelopment analysis based on a modified slack-based measure, and (2) a multi-choice goal programming approach. The contributions of this paper included the finding that rubber-tired gantry cranes are the greenest and should be used in ports. Finally, our findings aid port managers in selecting port equipment that provides the best balance between environmental protection and profitability.

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