Influence of intellectual capital and integration on operational performance: big data analytical capability perspectives

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chun-Hsi Vivian Chen ◽  
Yu-Cheng Chen
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Intellectual Capital ◽  
Structural Equation ◽  
Operational Performance ◽  
Equation Modeling ◽  
Content Type ◽  
Intangible Resources ◽  
Analytical Capability ◽  
Internal Integration

Purpose In the digital economy, as artificial intelligence applications increase, big data analytical capability (BDAC) plays a crucial role, and intellectual capital is growing in importance. This study aims to examine the possible benefits and effects of intellectual capital, BDAC and integrations on operational performance. Design/methodology/approach This study collected data from firms in Asia, and a total of 257 senior managers completed a questionnaire. Confirmatory factor analysis and structural equation modeling (SEM) is used for statistical analysis. Findings Intellectual capital positively correlates with BDAC, and BDAC positively relates to internal integration but not to external integration. Furthermore, both internal integration and external integration positively correlate with operational performance. This study supports that internal integration is a significant mediator in the influence of BDAC on operational performance. Practical implications First, the authors provide empirical evidence that intelligent capital in intangible resources helps firms to build BDAC. Second, this study stresses the importance of BDAC in business, which enhances the integration of the whole supply chain and results in superior operational performance. Originality/value This is a first attempt from the perspective of intelligent capital and uses SEM to emphasize the relationships among BDAC, supply chain integration and performance based on unique and irreplaceable intangible resources, thus providing a new perspective on the contributing factors of BDAC.

scholarly journals Impact of big data and predictive analytics capability on supply chain sustainability

2018 ◽  
Vol 29 (2) ◽  
pp. 513-538 ◽  
Author(s):  
Shirish Jeble ◽  
Rameshwar Dubey ◽  
Stephen J. Childe ◽  
Thanos Papadopoulos ◽  
David Roubaud ◽  
...  
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Theoretical Model ◽  
Performance Measures ◽  
Structural Equation ◽  
Predictive Analytics ◽  
Equation Modeling ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
The Impact

PurposeThe purpose of this paper is to develop a theoretical model to explain the impact of big data and predictive analytics (BDPA) on sustainable business development goal of the organization.Design/methodology/approachThe authors have developed the theoretical model using resource-based view logic and contingency theory. The model was further tested using partial least squares-structural equation modeling (PLS-SEM) following Peng and Lai (2012) arguments. The authors gathered 205 responses using survey-based instrument for PLS-SEM.FindingsThe statistical results suggest that out of four research hypotheses, the authors found support for three hypotheses (H1-H3) and the authors did not find support forH4. Although the authors did not find support forH4(moderating role of supply base complexity (SBC)), however, in future the relationship between BDPA, SBC and sustainable supply chain performance measures remain interesting research questions for further studies.Originality/valueThis study makes some original contribution to the operations and supply chain management literature. The authors provide theory-driven and empirically proven results which extend previous studies which have focused on single performance measures (i.e. economic or environmental). Hence, by studying the impact of BDPA on three performance measures the authors have attempted to answer some of the unresolved questions. The authors also offer numerous guidance to the practitioners and policy makers, based on empirical results.

A structural equation model for big data adoption in the healthcare supply chain

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Dindayal Agrawal ◽  
Jitender Madaan
Keyword(s):  
Factor Analysis ◽  
Big Data ◽  
Supply Chain ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Model ◽  
Equation Modeling ◽  
Data Governance ◽  
Social Perspective ◽  
Content Type

PurposeThe purpose of this study is to examine the barriers to the implementation of big data (BD) in the healthcare supply chain (HSC).Design/methodology/approachFirst, the barriers concerning BD adoption in the HSC were found by conducting a detailed literature survey and with the expert's opinion. Then the exploratory factor analysis (EFA) was employed to categorize the barriers. The obtained results are verified using the confirmatory factor analysis (CFA). Structural equation modeling (SEM) analysis gives the path diagram representing the interrelationship between latent variables and observed variables.FindingsThe segregation of 13 barriers into three categories, namely “data governance perspective,” “technological and expertise perspective,” and “organizational and social perspective,” is performed using EFA. Three hypotheses are tested, and all are accepted. It can be concluded that the “data governance perspective” is positively related to “technological and expertise perspective” and “organizational and social perspective” factors. Also, the “technological and expertise perspective” is positively related to “organizational and social perspective.”Research limitations/implicationsIn literature, very few studies have been performed on finding the barriers to BD adoption in the HSC. The systematic methodology and statistical verification applied in this study empowers the healthcare organizations and policymakers in further decision-making.Originality/valueThis paper is first of its kind to adopt an approach to classify barriers to BD implementation in the HSC into three distinct perspectives.

scholarly journals Understanding supply chain analytics capabilities and agility for data-rich environments

2019 ◽  
Vol 39 (6/7/8) ◽  
pp. 887-912 ◽  
Author(s):  
Samuel Fosso Wamba ◽  
Shahriar Akter
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Structural Equation ◽  
Equation Modeling ◽  
Future Research ◽  
Chain Management ◽  
Content Type ◽  
Supply Chain Agility ◽  
The Usa

Purpose Big data-driven supply chain analytics capability (SCAC) is now emerging as the next frontier of supply chain transformation. Yet, very few studies have been directed to identify its dimensions, subdimensions and model their holistic impact on supply chain agility (SCAG) and firm performance (FPER). Therefore, to fill this gap, the purpose of this paper is to develop and validate a dynamic SCAC model and assess both its direct and indirect impact on FPER using analytics-driven SCAG as a mediator. Design/methodology/approach The study draws on the emerging literature on big data, the resource-based view and the dynamic capability theory to develop a multi-dimensional, hierarchical SCAC model. Then, the model is tested using data collected from supply chain analytics professionals, managers and mid-level manager in the USA. The study uses the partial least squares-based structural equation modeling to prove the research model. Findings The findings of the study identify supply chain management (i.e. planning, investment, coordination and control), supply chain technology (i.e. connectivity, compatibility and modularity) and supply chain talent (i.e. technology management knowledge, technical knowledge, relational knowledge and business knowledge) as the significant antecedents of a dynamic SCAC model. The study also identifies analytics-driven SCAG as the significant mediator between overall SCAC and FPER. Based on these key findings, the paper discusses their implications for theory, methods and practice. Finally, limitations and future research directions are presented. Originality/value The study fills an important gap in supply chain management research by estimating the significance of various dimensions and subdimensions of a dynamic SCAC model and their overall effects on SCAG and FPER.

scholarly journals Environmental scanning, supply chain integration, responsiveness, and operational performance

2019 ◽  
Vol 39 (5) ◽  
pp. 787-814 ◽  
Author(s):  
Wantao Yu ◽  
Roberto Chavez ◽  
Mark Jacobs ◽  
Chee Yew Wong ◽  
Chunlin Yuan
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Business Environment ◽  
Supply Chain Integration ◽  
Operational Performance ◽  
Equation Modeling ◽  
Environmental Scanning ◽  
Content Type ◽  
Processing Theory ◽  
The Relationship

Purpose It remains unclear how environmental scanning (ES) can generate firm performance through supply chain management (SCM) practices. The purpose of this paper is to investigate the effects of ES on operational performance through supply chain integration (SCI) and supply chain responsiveness (SCR). Design/methodology/approach The scanning–interpretation–action–performance (SIAP) model and organization information processing theory (OIPT) are used to explain the ES–SCI–SCR–performance (S–I–A–P) relationships, which were tested by structural equation modeling of survey data of 329 manufacturing firms in China. Findings The results indicate that ES has a significant positive effect on SCI and SCR. SCI is significantly and positively related to SCR. SCR partially mediates the relationship between ES and operational performance, and fully mediates the relationship between SCI and operational performance. Practical implications Supply chain managers should collaborate with senior executives to obtain signals from ES activities, as input for building SCI and SCR and use SCI as a joint interpretation mechanism of ES signals for developing SCR to reap operational advantages in the rapidly changing business environment. Originality/value Strategic management academics and practitioners have explicitly emphasized the importance of ES in developing strategic plans but are unsure about the role of SCM in creating operational advantages through ES. Using the SIAP model, this study theorizes and demonstrates how SCI and SCR transform signals from ES into operational performance. In doing so, a more precise application of OIPT is explicated in the supply chain context.

Empirical analysis of enablers and performance outcome of manufacturing flexibility in an emerging economy

2020 ◽  
Vol 31 (6) ◽  
pp. 1301-1322 ◽  
Author(s):  
Ruchi Mishra
Keyword(s):  
Structural Equation ◽  
Positive Influence ◽  
Operational Performance ◽  
Equation Modeling ◽  
Extensive Literature ◽  
Product Mix ◽  
Content Type ◽  
Volume Flexibility ◽  
And Performance ◽  
Internal Integration

PurposeThe objective of this paper is to empirically test and verify the enablers of volume flexibility and product-mix flexibility and to assess the influence of these flexibilities on operational performance.Design/methodology/approachA research framework consisting of nine pairs of hypotheses was developed using an extensive literature review. Using a self-administered questionnaire, 391 responses were collected, and these responses were analyzed using descriptive statistics, factor analysis, and structural equation modeling techniques.FindingsThe findings empirically confirm the enablers of volume flexibility and product-mix flexibility. The proposed model explained 59 percent variance in volume flexibility and 63 percent variance in product-mix flexibility. Volume flexibility and product-mix flexibility together explained 38 percent variance in operational performance.Research limitations/implicationsTheoretically, this study advances flexibility literature in two significant ways. First, the study conducts first of its kind quantitative empirical investigation considering upstream, downstream, and internal integration practices as enablers of volume flexibility and product-mix flexibility. Second, this study adds to the flexibility literature by suggesting the positive influence of volume and product-mix flexibility on the operational performance of firms.Originality/valueThe study reinforces the role of enablers in the development of volume and product-mix flexibilities. Thus, the study provides a comprehensive view of flexibility enablers that can be used as a diagnostic tool, which practitioners can use to assess and deploy flexibility.

Achieving integration

2018 ◽  
Vol 29 (4) ◽  
pp. 1306-1324 ◽  
Author(s):  
Jessica L. Robinson ◽  
Karl Manrodt ◽  
Monique Lynn Murfield ◽  
Christopher A. Boone ◽  
Paige Rutner
Keyword(s):  
Supply Chain ◽  
Organizational Identification ◽  
Structural Equation ◽  
Spillover Effect ◽  
Equation Modeling ◽  
Content Type ◽  
Chain Orientation ◽  
Supplier Integration ◽  
Internal Integration ◽  
Supply Chain Orientation

PurposeThe purpose of this paper is to propose and test a dual pathway model whereby addressing the question, “What are the effects of supply chain orientation and organizational identification on internal integration and supplier integration?”.Design/methodology/approachA survey design was performed to collect data from supply chain professionals regarding their organization’s supply chain orientation (SCO), organizational identification (OI) and achieved states of both internal and supplier integration. Partial least squares-structural equation modeling was performed to test the dual mediating pathways.FindingsThe results show that internal integration partially mediates relationships between SCO and supplier integration and for OI and supplier integration. In comparing the mediating effects to test competing theories, the SCO path yields stronger complementary partial mediation. This supports the proposition that SCO and OI mutually exist within an organization and influence achieved integrative behaviors. Additionally, results suggest the behavioral spillover effect exists for an internally integrated organization that has also achieved supplier integration.Originality/valueThis research makes several contributions to extant literature, including finding that SCO contributes to levels of achieved integration. Also, this research theoretically integrates literature on the social dilemma associated with supplier integration and the behavioral spillover effect, suggesting that SCO allows for positive internal integrative behaviors to spillover to integrated suppliers. Finally, this research contributes to research on OI by finding achieved integration is an outcome, which refutes a dominate theory that explains OI facilitates negative behaviors toward external organizations.

Supply chain antecedents of agile manufacturing in a developing country context

2018 ◽  
Vol 29 (6) ◽  
pp. 1042-1064 ◽  
Author(s):  
Ayman Bahjat Abdallah ◽  
Israa Hussein Nabass
Keyword(s):  
Supply Chain ◽  
Developing Country ◽  
Structural Equation ◽  
Manufacturing Sector ◽  
Agile Manufacturing ◽  
Equation Modeling ◽  
Manufacturing Companies ◽  
Validity And Reliability ◽  
Content Type ◽  
Internal Integration

Purpose The purpose of this paper is to determine supply chain practices that contribute most to the success of agile manufacturing (AM), and to examine their effects on its implementation levels in the Jordanian manufacturing sector. It also investigates the effect of AM on operational performance (OP). Design/methodology/approach The study is based on survey data collected from 294 manufacturing companies from different industry types in Jordan. Validity and reliability analyses were performed using SPSS and AMOS, and the study hypotheses were tested using structural equation modeling. Findings The results revealed that supplier involvement, internal integration, and modularization of products positively and significantly affect AM. Customer involvement and postponement were insignificantly related to AM. Further, the results demonstrated that AM positively and significantly affect OP. Originality/value A limited number of previous studies investigated supply chain antecedents of AM. Further, there is no consensus among researchers on these practices. In addition, this area is underinvestigated in the developing countries in general and in Jordan in particular. The current study contributes to the literature by determining the most commonly linked supply chain practices to AM and examining their effects on its implementation levels in the context of a developing country, Jordan.

Exploring the role of intellectual capital in supply chain intelligence integration

2018 ◽  
Vol 118 (5) ◽  
pp. 1018-1032 ◽  
Author(s):  
Yongyi Shou ◽  
Wenjin Hu ◽  
Yongmei Xu
Keyword(s):  
Supply Chain ◽  
Intellectual Capital ◽  
Structural Equation ◽  
Design Methodology ◽  
Primary Data ◽  
Equation Modeling ◽  
Relational Capital ◽  
Content Type ◽  
Structural Capital

Purpose The purpose of this paper is to explore the role of intellectual capital (IC) in supply chain intelligence integration (SCII) and the interrelationships of the three components of IC (i.e. human capital (HC), structural capital (SC) and relational capital (RC)) in the supply chain context. Design/methodology/approach This paper conducted an empirical study by using primary data from 389 sample firms. The authors applied structural equation modeling to test the proposed hypotheses. Findings The results indicate that both HC and RC have direct impact on SCII, whereas SC only influences SCII through RC. Originality/value This study evidences that IC is an enabler of SCII. Furthermore, this study reveals the interrelationships of human, structural and RC.

Supply chain planning and trust: two sides of the same coin

2014 ◽  
Vol 114 (3) ◽  
pp. 405-420 ◽  
Author(s):  
Ely Laureano Paiva ◽  
Rafael Teixeira ◽  
Luciana Marques Vieira ◽  
Andrew Beheregaray Finger
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Operational Performance ◽  
Equation Modeling ◽  
Supply Chain Planning ◽  
Content Type ◽  
Manufacturing Management ◽  
Supply Planning ◽  
The Relationship

Purpose – The purpose of this paper is to analyze the relationship between supply planning, trust and integration, and the influence of them on operational performance. Design/methodology/approach – The paper used a survey with 335 respondents from three different industries. The paper analyzed the data with structural equation modeling. Findings – The results suggest that supply planning and trust are positively related and both influence supply integration and operational performance. At the end the paper proposed a classification for supply integration based on planning use and trust. Research limitations/implications – The sample is composed by companies from only three industries (machinery, electronics and automobile), what does not allow generalization. Practical implications – Managers are challenged to develop simultaneously supply chain planning practices and trust-based relationship within buyers and suppliers. They must pay attention to different integration drivers and use them accordingly and in the context analyzed. The study suggests a 2×2 matrix that might help managers’ decision making. Originality/value – Despite the importance of planning in supply and manufacturing management, few papers analyzed the role of supply planning integrated to trust. The combination between these aspects brings a more realistic and pragmatic view of the supply chain management.

Supply chain quality integration: relational antecedents and operational consequences

2018 ◽  
Vol 23 (3) ◽  
pp. 188-206 ◽  
Author(s):  
Yubing Yu ◽  
Baofeng Huo
Keyword(s):  
Supply Chain ◽  
Structural Equation ◽  
Operational Performance ◽  
Equation Modeling ◽  
Internal Quality ◽  
Relational Capital ◽  
Content Type ◽  
Holistic Perspective ◽  
Practical Implications ◽  
Positive Impacts

Purpose This paper aims to examine the impacts of relational capital on supply chain quality integration (SCQI) and operational performance from the holistic perspective of the entire supply chain. Design/methodology/approach Structural equation modeling with LISREL was used to test the conceptual model based on data collected from 308 companies in China. Findings The results indicate that with the exception of internal relational capital not having a significant impact on customer quality integration, supplier, internal and customer relational capital have positive impacts on supplier, internal and customer quality integration, which consequently improve operational performance. The results also show that internal relational capital has positive impacts on supplier and customer relational capital, and internal quality integration has positive impacts on supplier and customer quality integration. Practical implications The results provide important managerial insights for the improvement of operational performance through the development of relational capital and the implementation of SCQI practices throughout the supply chain. Originality/value The authors contribute to the relational capital and supply chain quality management literature by exploring the effectiveness of relational capital in improving SCQI and operational performance from the holistic perspective of the entire supply chain. The findings enrich the knowledge of SCQI management from the perspective of relational capital.

Sign in / Sign up

Export Citation Format

Share Document