Learning to Innovate with Big Data Analytics in Interorganizational Relationships

Browder, Russell E.; Koch, Hope; Long, Miss Anna; Hernandez, James S

doi:10.5465/amd.2019.0048

Cited by 13 publications

(10 citation statements)

References 85 publications

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“…However, supply chains are inherently inter-organizational, and the analytics used in such inter-organizational context needs examination. In a recent study of interorganizational relationships, Browder et al [116] state that BDA innovation process logic to be different with a focus on creating value through collective experimentation. Hence, future research is needed to further examine the value creation and business value of BDA with inter-organizational perspectives.…”

Section: Inter-organizational Big Data Analyticsmentioning

confidence: 99%

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Lee

Mangalaraj

2022

BDCC

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Big data analytics has been successfully used for various business functions, such as accounting, marketing, supply chain, and operations. Currently, along with the recent development in machine learning and computing infrastructure, big data analytics in the supply chain are surging in importance. In light of the great interest and evolving nature of big data analytics in supply chains, this study conducts a systematic review of existing studies in big data analytics. This study presents a framework of a systematic literature review from interdisciplinary perspectives. From the organizational perspective, this study examines the theoretical foundations and research models that explain the sustainability and performances achieved through the use of big data analytics. Then, from the technical perspective, this study analyzes types of big data analytics, techniques, algorithms, and features developed for enhanced supply chain functions. Finally, this study identifies the research gap and suggests future research directions.

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Section: Inter-organizational Big Data Analyticsmentioning

confidence: 99%

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Lee

Mangalaraj

2022

BDCC

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“…Based on this, we suggest that future OSCM research should consider the possibility of “residual gain” alongside residual loss that may accrue from contracting-out. This would be crucial to further understand the benefits of integrated relations such as alliances and partnering, and connects strongly with recent work exploring the value of collective experimentation between inter-organisational parties in new product/service development (Browder et al. , 2022).…”

Section: Discussionmentioning

confidence: 70%

Making agency theory work for supply chain relationships: a systematic review across four disciplines

Matinheikki

Kauppi

Brandon‐Jones

et al. 2022

IJOPM

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PurposeContemporary supply chain relationships inherently rely on delegation of work between organizations and, thus, are subject to agency problems for which a wide range of governance mechanisms exist. This review of agency theory (AT), across four distinct fields, explains the connection between governance mechanisms and supply chain relationship types.Design/methodology/approachThe study uses a systematic literature review (SLR) of articles using AT in a supply chain context from the operations and supply chain management, general management, marketing, and economics fields.FindingsThe authors categorize the governance mechanisms identified to create a typology of agency relationships in supply chains.Research limitations/implicationsThe developed typology provides parsimonious theory on different forms of supply chain agency relationships and takes a step towards a “supply chain-oriented agency theory” explaining and predicting relationship types and governance in supply chains. Furthermore, a future research agenda calls for more accurate measuring of agency costs, to examine residual gains alongside residual losses, to take a dual-sided perspective of agency relations and to adopt AT to examine more complex supply networks.Practical implicationsThe review provides a menu of governance mechanisms and describes situations under which these mechanisms could be deployed to guide managers when developing their supply chain relationships.Originality/valueThe first review to combine and elaborate views from four major disciplines using AT as a lens to supply chain relationships. Expanding the traditional set of governance mechanisms provides academics and practitioners with a bigger “menu” of options to consider.

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“…Another view of how BDA prompts innovation is that it departs from the standard IT service model, where IT delivers a solution to business units. With BDA projects, there is a level of uncertainty about what to “mine” in the data lake and how findings will be deployed, establishing collective experimentation as the mechanism for innovation (Browder et al ., 2022). Talent stays open to discoveries with BDA artifacts, often incomplete or influx by nature rather than a delivered solution, so beliefs around what is possible have fewer boundaries and more possible trajectories (Browder et al ., 2022).…”

Section: Theoretical Foundation and Hypothesesmentioning

confidence: 99%

Big data analytics: from leadership to firm performance

Koohang,

Sargent,

Zhang

et al. 2023

IMDS

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PurposeThis paper aims to propose a research model with eight constructs, i.e. BDA leadership, BDA talent quality, BDA security quality, BDA privacy quality, innovation, financial performance, market performance and customer satisfaction.Design/methodology/approachThe research model focuses on whether (1) Big Data Analytics (BDA) leadership influences BDA talent quality, (2) BDA talent quality influences BDA security quality, (3) BDA talent quality influences BDA privacy quality, (4) BDA talent quality influences Innovation and (5) innovation influences a firm's performance (financial, market and customer satisfaction). An instrument was designed and administered electronically to a diverse set of employees (N = 188) in various organizations in the USA. Collected data were analyzed through a partial least square structural equation modeling.FindingsResults showed that leadership significantly and positively affects BDA talent quality, which, in turn, significantly and positively impacts security quality, privacy quality and innovation. Moreover, innovation significantly and positively impacts firm performance. The theoretical and practical implications of the findings are discussed. Recommendations for future research are provided.Originality/valueThe study provides empirical evidence that leadership significantly and positively impacts BDA talent quality. BDA talent quality, in turn, positively impacts security quality, privacy quality and innovation. This is important, as these are all critical factors for organizations that collect and use big data. Finally, the study demonstrates that innovation significantly and positively impacts financial performance, market performance and customer satisfaction. The originality of the research results makes them a valuable addition to the literature on big data analytics. They provide new insights into the factors that drive organizational success in this rapidly evolving field.

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Learning to Innovate with Big Data Analytics in Interorganizational Relationships

Cited by 13 publications

References 85 publications

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Big Data Analytics in Supply Chain Management: A Systematic Literature Review and Research Directions

Making agency theory work for supply chain relationships: a systematic review across four disciplines

Big data analytics: from leadership to firm performance

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