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Incipient detection of pavement deterioration (such as crack identification) is critical to optimizing road maintenance because it enables preventative steps to be implemented to mitigate damage and possible failure. Traditional visual inspection has been largely superseded by semi-automatic/automatic procedures given significant advancements in image processing. Therefore, there is a need to develop automated tools to detect and classify cracks.

The literature review is employed to evaluate existing attempts to use Hough transform algorithm and highlight issues that should be improved. Then, developing a simple low-cost crack detection method based on the Hough transform algorithm for pavement crack detection and classification.

Analysis results reveal that model accuracy reaches 92.14% for vertical cracks, 93.03% for diagonal cracks and 95.61% for horizontal cracks. The time lapse for detecting the crack type for one image is circa 0.98 s for vertical cracks, 0.79 s for horizontal cracks and 0.83 s for diagonal cracks. Ensuing discourse serves to illustrate the inherent potential of a simple low-cost image processing method in automated pavement crack detection. Moreover, this method provides direct guidance for long-term pavement optimal maintenance decisions.

The outcome of this research can help highway agencies to detect and classify cracks accurately for a very long highway without a need for manual inspection, which can significantly minimize cost.

Hough transform algorithm was tested in terms of detect and classify a large dataset of highway images, and the accuracy reaches 92.14%, which can be considered as a very accurate percentage regarding automated cracks and distresses classification.

This article aims at - exploring and prioritizing the barriers to adoption of digitization in supply chains (SCs), categorizing them into sustainability triple bottom line (STBL) based upon their direct impact and suggesting digital technologies to address each barrier.

A five-phase methodology is used which consists of an exploration of 44 barriers to the adoption of digitization in SCs, analysis of 44 barriers for mean, standard deviation and Cronbach alpha based on questionnaire-based feedback of 25 experts, extraction of 10 most significant barriers through 05 experts, followed by categorization of the barriers into STBL referring to their direct impact on STBL, prioritization of ten barriers using Fuzzy Technique for Order Performance by Similarity to Ideal Solution and recommendation of digital technologies to address each barrier.

While all the barriers considered in this study significantly impede the adoption of digitization in SCs, lack of top management commitment (B1) is found to be most crucial while lack of culture toward use of information and communication technology required for digitization (B3) has minimum impact. Large investment in digital infrastructure (B6), difficulty in integration of cyber physical systems (CPSs) on varied platforms (B8) and lack of experts having knowledge of digital technologies (B2) are equally important barriers requiring more attention while adopting digitization in SCs.

This study is mainly based on feedback from 25 seasoned experts; a wider cross section of experts will give more insight.

The outcomes are very significant for organizations looking to adopt digitization in their SCs. Simultaneous consideration to all the barriers becomes impractical hence prioritization of same will be useful for the SC managers to benchmark their preparedness and decide strategies for the adoption of digitization with due consideration toward the impact of barriers on STBL. The digital technologies recommended will further aid in planning the digital strategies to address each barrier.

A unique approach to explore, analyze, prioritize and categorize the barriers to adoption of digitization in SCs is used to provide a deeper understanding of factors deterring the same. It implies that a supportive top management along with systematic allocation of finances plays a crucial role. The importance of availability of digital experts for integrating CPSs on a single platform is also highlighted. The digital technologies recommended will further assist the organizations toward adoption of digitization in SCs with due consideration to STBL.

The use of social media is an integral part of modern life, yet the impact of social media on creativity is a paradox. Drawing on the conservation of resources theory, the authors propose that social media, as an ecological condition, both nurture and deplete resources. Accordingly, the authors investigated two inconsistent mechanisms: creative self-efficacy and ego depletion.

Study 1 established the within-person effects of social media use on creativity by tracking 64 college students for five working days. Using a sample of 493 employee–leader-matched dyads in a national bank, Study 2 tested the entire model. Study 3 is a follow-up experiment based on a sample of 160 participants.

The results consistently showed that: (1) social media use had a positive impact on creativity in general; (2) social media use increased ego depletion and creative self-efficacy, which were two inconsistent mediators; (3) hedonic use of social media reduced the negative impact of cognitive use of social media on ego depletion.

This research sheds new light on the paradox between social media use and creativity and highlights the benefits of the balanced use of social media features. This research has implications for creative stimulation and job design in digital contexts.

This paper aims to provide a starting point to discuss how social enterprises can drive systemic change in terms of social impact through operations and supply chain management.

This paper reviews existing literature and the four papers in this special issue and develops a conceptual framework of how social enterprises and their supply chains create social impact and further enable systematic change.

Our paper finds that social impact and systemic change can be shaped by social enterprises at three different levels of analysis (organization, supply chain and context) and through three enablers (cognitive shift, stakeholder collaboration and scalability). Such dimensions are used to position current literature and to highlight new research directions.

This paper proposes a novel understanding of operations and supply chain management in social enterprises intended as catalysts for systemic change. Based on this premise we distinguish different practices and stakeholders to be considered when studying social impact at different levels. The conceptual framework introduced in the paper provides a new pathway for future research and debate by scholars engaged at the intersection of social impact, sustainable operations and supply chain management.