Dynamics between blockchain adoption determinants and supply chain performance: An empirical investigation

Abstract The logistics and supply chain management (SCM) field is experimenting with the integration of blockchain, a cutting-edge, and highly disruptive technology. Yet, blockchain is still nascent, and the extant literature on this technology is scarce, especially as regards the relationship between blockchain and SCM. Additionally, existing studies have not yet addressed sufficiently the enablers of blockchain adoption and the interplay with supply chain performance. In order to reduce this gap, this study aims to examine the potential influence of blockchain on supply chain performance. We draw on the literature on technology adoption and supply chain performance, as well as on the emerging blockchain literature, to develop and test a model in two countries, namely India and the US. Accordingly, we administered a survey in order to review the opinions and views of supply chain practitioners. The results support the model and indicate that blockchain applications can improve supply chain performance. In particular, our findings suggest that knowledge sharing and trading partner pressure play an important role in blockchain adoption, and that supply chain performance is significantly influenced by supply chain transparency and blockchain transparency. Another finding was the inexistence of evidence for a moderation effect of the industry variable on the outcomes. The research conclusions have substantial managerial and theoretical implications. Our model contributes mainly to the theoretical advancement of SCM-blockchain, thus allowing scholars to adapt our validated model.

[1]  Carmel McNaught,et al.  How academics use technology in teaching and learning: understanding the relationship between beliefs and practice , 2006, J. Comput. Assist. Learn..

[2]  Achim Kienle,et al.  Integrated Simulated Moving Bed Processes for Production of Single Enantiomers , 2011 .

[3]  Monideepa Tarafdar,et al.  Supply chain information systems strategy: Impacts on supply chain performance and firm performance , 2014 .

[4]  Joshua Ignatius,et al.  Assessing Knowledge Sharing Among Academics: A Validation of the Knowledge Sharing Behavior Scale (KSBS) , 2014, Evaluation review.

[5]  Angappa Gunasekaran,et al.  Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications , 2019 .

[6]  Viswanath Venkatesh,et al.  Managing Citizens' Uncertainty in E-Government Services: The Mediating and Moderating Roles of Transparency and Trust , 2016, Inf. Syst. Res..

[7]  Kefeng Xu,et al.  INFORMATION GAMING IN DEMAND COLLABORATION AND SUPPLY CHAIN PERFORMANCE , 2004 .

[8]  Mehmet A. Orgun,et al.  A Proof-of-Trust Consensus Protocol for Enhancing Accountability in Crowdsourcing Services , 2019, IEEE Transactions on Services Computing.

[9]  Chinyao Low,et al.  Understanding the determinants of cloud computing adoption , 2011, Ind. Manag. Data Syst..

[10]  N. Kshetri Blockchain's roles in strengthening cybersecurity and protecting privacy , 2017 .

[11]  Nigel Caldwell,et al.  Transparency in Supply Relationships: Concept and Practice , 2001 .

[12]  Terence L. Holmes,et al.  Effects of relationalism and readiness on EDI collaboration and outcomes , 1999 .

[13]  J. Hox,et al.  A checklist for testing measurement invariance , 2012 .

[14]  Viswanath Venkatesh,et al.  Blockchain, adoption, and financial inclusion in India: Research opportunities , 2020, Int. J. Inf. Manag..

[15]  Alexander E. Ellinger,et al.  Supplier transparency: scale development and validation , 2018, The International Journal of Logistics Management.

[16]  Michael R. Mullen,et al.  Structural equation modelling: guidelines for determining model fit , 2008 .

[17]  Malin Song,et al.  Blockchain technology and enterprise operational capabilities: An empirical test , 2020, Int. J. Inf. Manag..

[18]  Angappa Gunasekaran,et al.  Understanding the Blockchain technology adoption in supply chains-Indian context , 2018, Int. J. Prod. Res..

[19]  Thomas J. Goldsby,et al.  In Search of Research Ideas? Call a Professional , 2017 .

[20]  S. Borgatti,et al.  On Social Network Analysis in a Supply Chain Context , 2009 .

[21]  Li Jiang,et al.  Trust and Electronic Government Success: An Empirical Study , 2008, J. Manag. Inf. Syst..

[22]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[23]  Hsiu-Fen Lin Antecedents and consequences of electronic supply chain management diffusion , 2017 .

[24]  Angappa Gunasekaran,et al.  Modeling the blockchain enabled traceability in agriculture supply chain , 2020, Int. J. Inf. Manag..

[25]  Judith M. Whipple,et al.  Managing Internal Supply Chain Integration: Integration Mechanisms and Requirements , 2017 .

[26]  Samuel Fosso Wamba,et al.  Blockchain adoption challenges in supply chain: An empirical investigation of the main drivers in India and the USA , 2019, Int. J. Inf. Manag..

[27]  Wynne W. Chin,et al.  Multi-group Invariance Testing: An Illustrative Comparison of PLS Permutation and Covariance-Based SEM Invariance Analysis , 2014 .

[28]  Petri Helo,et al.  Blockchains in operations and supply chains: A model and reference implementation , 2019, Comput. Ind. Eng..

[29]  Lucas Santos Dalenogare,et al.  Industry 4.0 technologies: Implementation patterns in manufacturing companies , 2019, International Journal of Production Economics.

[30]  P. M. Podsakoff,et al.  Self-Reports in Organizational Research: Problems and Prospects , 1986 .

[31]  C. Wong,et al.  Towards a theory of multi-tier sustainable supply chains: a systematic literature review , 2014 .

[32]  Paolo Tasca,et al.  Blockchain Technologies: The Foreseeable Impact on Society and Industry , 2017, Computer.

[33]  Chad W. Autry,et al.  Relational and Process Multiplexity in Vertical Supply Chain Triads: An Exploration in the U.S. Restaurant Industry , 2014 .

[34]  Kim-Kwang Raymond Choo,et al.  A blockchain future for internet of things security: a position paper , 2017, Digit. Commun. Networks.

[35]  Henrik S. Sternberg,et al.  Distributed ledger technology in supply chains: a transaction cost perspective , 2020, Int. J. Prod. Res..

[36]  Zhuming Bi,et al.  Blockchain-based business process management (BPM) framework for service composition in industry 4.0 , 2018, Journal of Intelligent Manufacturing.

[37]  Mir Saman Pishvaee,et al.  Integrated innovative product design and supply chain tactical planning within a blockchain platform , 2020, Int. J. Prod. Res..

[38]  Gareth R. T. White Future applications of blockchain in business and management: A Delphi study , 2017 .

[39]  Yichuan Wang,et al.  People, Technologies, and Organizations Interactions in a Social Commerce Era , 2017, IEEE Transactions on Engineering Management.

[40]  Yogesh Kumar Dwivedi,et al.  Land records on Blockchain for implementation of Land Titling in India , 2020, Int. J. Inf. Manag..

[41]  P. Beynon-Davies,et al.  Understanding blockchain technology for future supply chains: a systematic literature review and research agenda , 2019, Supply Chain Management: An International Journal.

[42]  Volodymyr Babich,et al.  Distributed Ledgers and Operations: What Operations Management Researchers Should Know About Blockchain Technology , 2018 .

[43]  Naresh K. Malhotra,et al.  Common Method Variance in IS Research: A Comparison of Alternative Approaches and a Reanalysis of Past Research , 2006, Manag. Sci..

[44]  David Swanson,et al.  The Supply Chain Has No Clothes: Technology Adoption of Blockchain for Supply Chain Transparency , 2018 .

[45]  Joe B. Hanna,et al.  Supply chain management research: Key elements of study design and statistical testing , 2015 .

[46]  Arnab Banerjee,et al.  Chapter Three - Blockchain Technology: Supply Chain Insights from ERP , 2018, Adv. Comput..

[47]  Yan Chen,et al.  Blockchain Tokens and the Potential Democratization of Entrepreneurship and Innovation , 2017, Business Horizons.

[48]  Shouki A. Ebad An exploratory study of ICT projects failure in emerging markets , 2018 .

[49]  David A. Griffith,et al.  Knowledge Management in Supply Chains: The Role of Explicit and Tacit Knowledge , 2014 .

[50]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[51]  Xiwei Xu,et al.  Adaptable Blockchain-Based Systems: A Case Study for Product Traceability , 2017, IEEE Software.

[52]  Gary Garrison,et al.  Understanding users' behaviors regarding supply chain technology: Determinants impacting the adoption and implementation of RFID technology in South Korea , 2010, Int. J. Inf. Manag..

[53]  Kai Spohrer,et al.  A Blockchain Research Framework , 2017, Business & Information Systems Engineering.

[54]  Partha Priya Datta,et al.  Supply network resilience: a systematic literature review and future research , 2017 .

[55]  L. Trinchera,et al.  A Distribution Free Interval Estimate for Coefficient Alpha , 2018 .

[56]  K. Mardia Measures of multivariate skewness and kurtosis with applications , 1970 .

[57]  A. Abubakar,et al.  Knowledge management, decision-making style and organizational performance , 2017, Journal of Innovation & Knowledge.

[58]  A. Satorra,et al.  A scaled difference chi-square test statistic for moment structure analysis , 1999 .

[59]  Scott B. MacKenzie,et al.  Recommendations for Creating Better Concept Definitions in the Organizational, Behavioral, and Social Sciences , 2016 .

[60]  Tiago Oliveira,et al.  An empirical analysis to assess the determinants of SaaS diffusion in firms , 2016, Comput. Hum. Behav..

[61]  Scott J. Grawe,et al.  Enhancing dyadic performance through boundary spanners and innovation: An assessment of service provider-customer relationships , 2015 .

[62]  Yogesh Kumar Dwivedi,et al.  An empirical validation of a unified model of electronic government adoption (UMEGA) , 2017, Gov. Inf. Q..

[63]  Dara G. Schniederjans,et al.  Supply chain digitisation trends: An integration of knowledge management , 2020 .

[64]  Benjamin T. Hazen,et al.  How supply chain analytics enables operational supply chain transparency , 2018 .

[65]  Yu Min Wang,et al.  Understanding the determinants of RFID adoption in the manufacturing industry , 2010 .

[66]  Fabrizio Dabbene,et al.  Traceability issues in food supply chain management: A review , 2014 .

[67]  Ravinder Nath,et al.  An empirical study of EDI trading partner selection criteria in customer-supplier relationships , 2000, Inf. Manag..

[68]  Giovanni Mirabelli,et al.  The Global Track&Trace System for food: General framework and functioning principles , 2015 .

[69]  Yogesh Kumar Dwivedi,et al.  Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model , 2017, Information Systems Frontiers.

[70]  J. Makhoul,et al.  Linear prediction: A tutorial review , 1975, Proceedings of the IEEE.

[71]  Nir Kshetri,et al.  1 Blockchain's roles in meeting key supply chain management objectives , 2018, Int. J. Inf. Manag..

[72]  V. Venkatesh,et al.  Unified Theory of Acceptance and Use of Technology: U.S. Vs. China , 2010 .

[73]  David E. Cantor,et al.  How Environmental Management Competitive Pressure Affects a Focal Firm's Environmental Innovation Activities: A Green Supply Chain Perspective , 2015 .

[74]  Muhammad Shoaib Farooq,et al.  Acceptance and use of lecture capture system (LCS) in executive business studies: Extending UTAUT2 , 2017, Interact. Technol. Smart Educ..

[75]  C. Fornell,et al.  Evaluating Structural Equation Models with Unobservable Variables and Measurement Error , 1981 .

[76]  Joseph F. Hair,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .

[77]  Henry M. Kim,et al.  Towards an Ontology-Driven Blockchain Design for Supply Chain Provenance , 2016, Intell. Syst. Account. Finance Manag..

[78]  Jeannette Paschen,et al.  How blockchain technologies impact your business model , 2019, Business Horizons.

[79]  Feng Tian,et al.  A supply chain traceability system for food safety based on HACCP, blockchain & Internet of things , 2017, 2017 International Conference on Service Systems and Service Management.

[80]  Thomas J. Goldsby,et al.  Technology Innovation and New Business Models: Can Logistics and Supply Chain Research Accelerate the Evolution? , 2016 .

[81]  Donna F. Davis,et al.  Examining Market Information and Brand Equity Through Resource-Advantage Theory: A Carrier Perspective , 2012 .

[82]  Garry Wei-Han Tan,et al.  Time to seize the digital evolution: Adoption of blockchain in operations and supply chain management among Malaysian SMEs , 2020, Int. J. Inf. Manag..

[83]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[84]  Albert Maydeu-Olivares Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit , 2017 .

[85]  Fred D. Davis Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[86]  Stefan Tönnissen,et al.  Analysing the impact of blockchain-technology for operations and supply chain management: An explanatory model drawn from multiple case studies , 2020, Int. J. Inf. Manag..

[87]  Benjamin T. Hazen,et al.  A Trail Guide to Publishing Success: Tips on Writing Influential Conceptual, Qualitative, and Survey Research , 2014 .

[88]  Kenneth A. Bollen,et al.  Structural Equations with Latent Variables , 1989 .

[89]  Gordon W. Cheung,et al.  Assessing Extreme and Acquiescence Response Sets in Cross-Cultural Research Using Structural Equations Modeling , 2000 .

[90]  Yingli Wang,et al.  Making sense of blockchain technology: How will it transform supply chains? , 2019, International Journal of Production Economics.

[91]  Charles Makanyeza,et al.  Consumers’ acceptance and use of plastic money in Harare, Zimbabwe , 2018 .

[92]  Chun-Liang Chen Value Creation by SMEs Participating in Global Value Chains under Industry 4.0 Trend: Case Study of Textile Industry in Taiwan , 2019, Journal of Global Information Technology Management.

[93]  Nir Kshetri,et al.  Potential roles of blockchain in fighting poverty and reducing financial exclusion in the global south , 2017 .

[94]  Li Da Xu,et al.  Industry 4.0: state of the art and future trends , 2018, Int. J. Prod. Res..

[95]  Riccardo Mazza,et al.  Unified Theory of Acceptance and Use of Technology (UTAUT) for Market Analysis of FP7 CHOReOS Products , 2013 .

[96]  Manuel Díaz,et al.  On blockchain and its integration with IoT. Challenges and opportunities , 2018, Future Gener. Comput. Syst..

[97]  Jialin Yi A measure of knowledge sharing behavior: scale development and validation , 2009 .

[98]  Rayees Farooq,et al.  A conceptual model of knowledge sharing , 2018 .

[99]  D. Ketchen A Primer on Partial Least Squares Structural Equation Modeling , 2013 .

[100]  David M. Gligor,et al.  A Cross‐Disciplinary Examination of Firm Orientations’ Performance Outcomes: The Role of Supply Chain Flexibility , 2014 .

[101]  Francesco Longo,et al.  Blockchain-enabled supply chain: An experimental study , 2019, Comput. Ind. Eng..

[102]  M. Sarstedt,et al.  A new criterion for assessing discriminant validity in variance-based structural equation modeling , 2015 .

[103]  Ahm Shamsuzzoha,et al.  Real-time supply chain - A blockchain architecture for project deliveries , 2020, Robotics Comput. Integr. Manuf..

[104]  Vallipuram Muthukkumarasamy,et al.  Blockchain based wine supply chain traceability system , 2017 .

[105]  Yingli Wang,et al.  ICT in multimodal transport and technological trends: unleashing potential for the future , 2015 .

[106]  James H. Steiger,et al.  Understanding the limitations of global fit assessment in structural equation modeling , 2007 .

[107]  R. Klassen,et al.  The impact of supply chain structure on the use of supplier socially responsible practices , 2010 .

[108]  Yves Rosseel,et al.  lavaan: An R Package for Structural Equation Modeling , 2012 .

[109]  Thomas J. Goldsby,et al.  The Role of Academic Research in Supply Chain Practice: How Much Are We Contributing? , 2017 .

[110]  Constantin Blome,et al.  Does Sustainable Supplier Cooperation Affect Performance , 2012 .

[111]  Thomas Y. Choi,et al.  Toward the Theory of the Supply Chain , 2015 .

[112]  R. Monfared,et al.  Blockchain ready manufacturing supply chain using distributed ledger , 2016 .

[113]  Thomas Y. Choi,et al.  Supply Networks: Theories and Models , 2008 .

[114]  Weidong Shi,et al.  Blockchain in global supply chains and cross border trade: a critical synthesis of the state-of-the-art, challenges and opportunities , 2019, Int. J. Prod. Res..

[115]  V. Daniel R. Guide,et al.  Notes from the Editors: Redefining some methodological criteria for the journal ☆ , 2015 .

[116]  Towards an Ontology-Driven Blockchain Design for Supply Chain Provenance , 2016 .

[117]  A. Satorra,et al.  Corrections to test statistics and standard errors in covariance structure analysis. , 1994 .

[118]  Gülçin Büyüközkan,et al.  Digital Supply Chain: Literature review and a proposed framework for future research , 2018, Comput. Ind..

[119]  R. Singh Modelling of critical factors for responsiveness in supply chain , 2015 .

[120]  Suling Jia,et al.  Digital enablement of blockchain: Evidence from HNA group , 2018, Int. J. Inf. Manag..

[121]  A. Hu,et al.  Critical factors for implementing green supply chain management practice , 2010 .

[122]  S. Fawcett,et al.  The SCM Knowledge Supply Chain: Integrating World Views to Advance the Discipline , 2014 .

[123]  Albert H. Segars,et al.  Knowledge Management: An Organizational Capabilities Perspective , 2001, J. Manag. Inf. Syst..

[124]  Marijn Janssen,et al.  Boundary conditions for traceability in food supply chains using blockchain technology , 2020, Int. J. Inf. Manag..

[125]  F. Chen Sensitivity of Goodness of Fit Indexes to Lack of Measurement Invariance , 2007 .

[126]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[127]  Gordon W. Cheung,et al.  Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance , 2002 .

[128]  S. Bonilla,et al.  Blockchain and supply chain management integration: a systematic review of the literature , 2019, Supply Chain Management: An International Journal.

[129]  Tatsuo Nakajima,et al.  A novel approach to solve a mining work centralization problem in blockchain technologies , 2018, Int. J. Pervasive Comput. Commun..

[130]  Yogesh Kumar Dwivedi,et al.  Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust , 2017, Int. J. Inf. Manag..

[131]  Alexandre Dolgui,et al.  Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain , 2019, Int. J. Prod. Res..

[132]  Patricia J. Daugherty,et al.  Knowledge Synthesis and Innovative Logistics Processes: Enhancing Operational Flexibility and Performance , 2011 .

[133]  Henry M. Kim,et al.  A Perspective on Blockchain Smart Contracts: Reducing Uncertainty and Complexity in Value Exchange , 2017, 2017 26th International Conference on Computer Communication and Networks (ICCCN).

[134]  Constantin Blome,et al.  Does sustainable supplier co-operation affect performance? Examining implications for the triple bottom line , 2012 .

[135]  P. Bentler,et al.  Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives , 1999 .

[136]  Angappa Gunasekaran,et al.  Determinants of RFID adoption intention by SMEs: an empirical investigation , 2016 .

[137]  M. Lindell,et al.  Accounting for common method variance in cross-sectional research designs. , 2001, The Journal of applied psychology.

[138]  Thomas Y. Choi,et al.  Supply networks and complex adaptive systems: Control versus emergence , 2001 .

[139]  T. Choi,et al.  Information disclosure structure in supply chains with rental service platforms in the blockchain technology era , 2020 .

[140]  T Raykov,et al.  Estimation of congeneric scale reliability using covariance structure analysis with nonlinear constraints. , 2001, The British journal of mathematical and statistical psychology.

[141]  Rima Kilany,et al.  The power of a blockchain-based supply chain , 2019, Comput. Ind. Eng..

[142]  Rui-Yang Chen,et al.  A traceability chain algorithm for artificial neural networks using T-S fuzzy cognitive maps in blockchain , 2018, Future Gener. Comput. Syst..

[143]  Stephan M. Wagner,et al.  Blockchain and supply chain relations: A transaction cost theory perspective , 2019, Journal of Purchasing and Supply Management.

[144]  John T. Mentzer,et al.  Forecasting Technique Familiarity, Satisfaction, Usage, and Application , 1995 .

[145]  George Q. Huang,et al.  Toward open manufacturing: A cross-enterprises knowledge and services exchange framework based on blockchain and edge computing , 2017, Ind. Manag. Data Syst..

[146]  Joseph Sarkis,et al.  Blockchain technology and its relationships to sustainable supply chain management , 2018, Int. J. Prod. Res..

[147]  Stephan M. Wagner,et al.  AN EMPIRICAL EXAMINATION OF SUPPLY CHAIN PERFORMANCE ALONG SEVERAL DIMENSIONS OF RISK , 2008 .

[148]  Yogesh Kumar Dwivedi,et al.  Blockchain research, practice and policy: Applications, benefits, limitations, emerging research themes and research agenda , 2019, Int. J. Inf. Manag..

[149]  Hsiu-Fen Lin,et al.  Interorganizational and organizational determinants of planning effectiveness for Internet-based interorganizational systems , 2006, Inf. Manag..

[150]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research , 2014 .