Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance

Bag, Surajit; Luthra, Sunil; Mangla, Sachin Kumar; Kazançoğlu, Yiğit

doi:10.1108/ijlm-06-2020-0237

Cited by 24 publications

(14 citation statements)

References 94 publications

(127 reference statements)

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“…Our study revealed that the BDCC of BDAC both directly affects innovative performance and mediates the relationship between BDU and IOP. These findings support previous studies (Bag et al, 2021;Buhalis & Volchek, 2021;Ciampi et al, 2021;Côrte-Real et al, 2017).…”

Section: Discussionsupporting

confidence: 93%

“…BDACs provide a competitive edge (Bag et al, 2021; Gupta et al, 2020), including in international tourism markets (Aakash & Gupta Aggarwal, 2020; Yasar & Demir, 2019). As part of BDAC, big data can be collected to identify changing customer trends, employee expectations, the sustainability of relations with stakeholders and the hotel's social image.…”

Section: Discussionmentioning

confidence: 99%

“…This 10‐item scale measured the five features of big data (i.e., variety, velocity, volume, veracity and value). It was developed from the literature (Bag et al, 2021; Hodgkinson & Sadler‐Smith, 2018; Nisar et al, 2020; Shamim et al, 2019) and had good psychometric properties, as seen in Table 1. The Cronbach alpha of the first pilot test was .77 ( p = .014), whereas the Cronbach alpha of the second pilot test was .82 ( p = .008).…”

Section: Methodsmentioning

confidence: 99%

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Big data and innovative organizational performance: Evidence from a moderated‐mediated model

Demir

YAŞAR

2022

Creat Innov Manage

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Big data in hotels is crucial in new business models, processes and methods for improving innovative organizational performance. This study investigates how big data and its sharing directly impact innovative organizational performance through big data analytics capabilities. Research data collected from 438 participants at 36 five-star hotels were analysed using structural equation models. The analysis found that using and sharing big data in hotels directly affects big data analytics capabilities and innovative organizational performance. Furthermore, analytical capacities mediate between using and sharing big data and creative organizational performance.These results have some theoretical and practical implications.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Big data and innovative organizational performance: Evidence from a moderated‐mediated model

Demir

YAŞAR

2022

Creat Innov Manage

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“…5 Big data also help decision-making accuracy within an organization, 6 the fourth paradigm of science, 7 maximizing innovation performance, 8 and reducing expenses. 9…”

Section: Introductionmentioning

confidence: 99%

“…5 Big data also help decision-making accuracy within an organization, 6 the fourth paradigm of science, 7 maximizing innovation performance, 8 and reducing expenses. 9 Some scholars argue that investing in BDAC is a fallacy since by using this talent, a company's innovation performance has improved, even if BDAC has changed from a more traditional organization to one that does innovation work. 10,11 Organizations are expected to use effective innovation technology to maintain adequate productivity levels in their environments.…”

Section: Introductionmentioning

confidence: 99%

The impact of big data analytics on organizational sustainability: The influencing factors of autonomous research and development and absorptive capacity

Arshad

Qadir

et al. 2022

International Journal of Engineering Business Management

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This study aims to see how the big data analytics capability (BDAC) and its dimensions affect the absorptive capacity and autonomous R&D of high-speed railways. As well as their impact on the organization’s long-term sustainability, using the mediation of absorptive capacity and autonomy in R&D. Employees and the heads of the planning, HR, R&D, and technical departments of high-speed railways were polled for information. For data analysis, we used PLS-SEM, and then we employed mediation analysis. BDAC increases the organization’s ability to tolerate change and gives management instructions on making decisions. This study adds to the body of knowledge on absorptive capacity development and autonomy over R&D activities by investigating the role of BDAC in the long-term development of high-speed trains.

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Data‐driven insights for circular and sustainable food supply chains: An empirical exploration of big data and predictive analytics in enhancing social sustainability performance

Bag,

Srivastava,

Cherrafi

et al. 2023

Bus Strat Env

Self Cite

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Although the circular economy is commonly used among industries in developing countries to achieve carbon neutrality targets, its impact on social sustainability must be clarified. Stakeholders (for instance, community stakeholders) have been observed to be unaware of the focal firm's circular supply chain activities. Because this gap has not been generally reflected in the literature, it is critical to perform an empirical study to bridge the gap between theory and practice. The goal of this research was to determine whether new technologies such as big data and predictive analytics might influence an organization's propensity to share information related to circular economy practices with stakeholders as well as to increase connectivity with those stakeholders in the Industry 4.0 era. We also investigated whether these actions could increase stakeholder trust and engagement and social sustainability as a result. We tested our theoretical model using samples from food supply chain firms in South Africa. Confirmatory factor analysis was conducted using WarpPLS 7.0 software. The findings show that firms that deploy big data and predictive analytics are more likely to share information related to the circular economy with stakeholders and that these firms are also well‐connected with those stakeholders, resulting in increased trust and engagement. This, in turn, contributes to the social sustainability of supply chains. Our research has made a significant contribution by encouraging a theoretical debate regarding the willingness to share information regarding the circular economy and the social sustainability of the supply chain.

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Leveraging big data analytics capabilities in making reverse logistics decisions and improving remanufacturing performance

Cited by 24 publications

References 94 publications

Big data and innovative organizational performance: Evidence from a moderated‐mediated model

Big data and innovative organizational performance: Evidence from a moderated‐mediated model

The impact of big data analytics on organizational sustainability: The influencing factors of autonomous research and development and absorptive capacity

Data‐driven insights for circular and sustainable food supply chains: An empirical exploration of big data and predictive analytics in enhancing social sustainability performance

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