Exploring the mutual influence among the social innovation factors amid the COVID-19 pandemic.

Hadi Badri Ahmadi, Huai-Wei Lo, Pourya Pourhejazy, Himanshu Gupta, James J H Liou

Abstract read

In one paragraph

Article in Applied soft computing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

Diffusion of Social Innovation: the Innovation Provider's Perspective.Journal of the knowledge economy · 2023
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Hadi Badri AhmadiDepartment of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.

Huai-Wei LoDepartment of Business Administration, Chaoyang University of Technology, Taichung, Taiwan.

Pourya PourhejazyDepartment of Industrial Engineering, UiT- The Arctic University of Norway, Lodve Langsgate 2, Narvik 8514, Norway.

Himanshu GuptaDepartment of Management Studies, Indian Institute of Technology (Indian School of Mines), Dhanbad, India.

James J H LiouDepartment of Industrial Engineering and Management, National Taipei University of Technology, Taipei 10608, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

From the triple bottom line, the social aspect has received relatively limited attention during the Corona Virus Disease (COVID-19) pandemic, particularly in the emerging economies. Social innovation factors help improve the sustainability performance of the companies. This study develops a social innovation decision framework and analyses the interrelationships among social innovation factors considering the COVID-19 situation. For this purpose, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) is extended by integrating the Z numbers and rough fuzzy set theory into its computational procedure. Z-numbers address the uncertainty of the decision and experts' confidence in the evaluation and rough numbers are used for aggregating the experts' opinions. On this basis, the mutual influence of social innovation factors and the influence weights of these factors are investigated. The results suggest that a quick response to market demand for sustainable products is the most influential factor in attaining social sustainability innovation during the pandemic. This article is concluded by providing insights for industrial experts and decision-makers to understand the underpinnings of social sustainability innovation during unforeseen situations.

Indexed as

COVID-19 pandemicDecision analysisRough numbersSocial innovationSupply chain managementSustainability

Identifiers

PMID35755298

DOI10.1016/j.asoc.2022.109157

PMCPMC9212814

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.