Hazen et al. (2014)/International Journal of Production Economics |
Studying the importance of data quality in supply chain management decisions |
Statistical process control / Field study |
Remanufacturing company for jet engines and related components for military aircraft |
527 |
-Developing new methods for controlling data |
Chen et al. (2015)/Journal of Management Information Systems |
Studying the role of big data analytics in value creation and competitive advantage |
Technological, organizational, and environmental (TOE) framework |
Collected data from supply chain executives through a questionnaire |
192 |
-Examining the influence of firm-level employment of big data analytics on organizational performance |
-Examining the intervening variables between organizational IT practices and performance outcomes |
Tan et al. (2015)/International Journal of Production Economics |
Providing firms an analytic infrastructure to combine their competence sets |
Deduction graph technique |
SPEC company, a leading eyeglasses manufacturer in China |
252 |
-Testing the contributed approach on other supply chains to determine its general applicability |
-Simplifying the contributed mathematical approach |
Giannakis & Louis (2016)/Journal of Enterprise Information Management |
Developing a big data analytics system that exerts autonomous corrective control actions in a supply chain |
Analytical study / Supply chain agility theories |
NA |
77 |
-Studying the application of an agent-based technology in supply chain sustainability |
-Studying the influence of the attributes of supply chain managers on the implementation of agent-based technology in decision making |
Prasad et al. (2018)/Annals of Operations Research |
Developing a model to connect big data analytics to superior humanitarian outcomes |
Resource dependence theory |
Three focal non-governmental organizations’ supply network in India |
42 |
-Doing research to clearly identify stages regarding big data attributes |
-Examining the scenarios of non-linear patterns emanating from distributed supply chain networks |
Richey Junior et al. (2016)/International Journal of Physical Distribution & Logistics Management |
Developing a framework in which supply chain managers can use big data |
Native category approach |
Interviewing 27 supply chain experts in 6 countries |
68 |
-Developing unbiased managerial guidance for using big data analytics in supply chain management |
Gunasekaran et al. (2017)/Journal of Business Research |
Studying the impact of big data and predictive analytics on supply chain performance |
Statistical analysis / Field study |
E-mail survey of a sample of companies in India |
279 |
-Investigating top managers’ commitment towards developing big data predictive analytics capabilities |
Kache & Seuring (2017)/International Journal of Operations & Production Management |
Investigating the impacts of big data analytics on information usage in a supply chain |
Delphi survey / Statistical analysis |
Collect data from 15 experts by questionnaire |
195 |
-Studying the constituents of a big data ecosystem as keys for optimal supply chain productivity |
Roßmann et al. (2018)/Technological Forecasting and Social Change |
Studying expert assessments of big data analytics applications in supply chain management |
Delphi survey / Fuzzy c-means clustering |
Interview with 73 experts |
38 |
-Interviewing other fields’ experts |
-Studying the impact of potential technological applications on social dynamics in supply chain management |
Choi (2018)/Transportation Research Part E |
Studying the impact of social media comments on quick response supply chains in fashion |
Analytical mathematical modeling / Newsvendor model |
NA |
30 |
-Incorporate the correlation of consumer voices and a product’s demand |
-Studying the impact of a government’s role in local sourcing and emissions taxes on a supplier-market relationship |
Coble et al. (2018)/Applied Economic Perspectives and Policy |
Studying the challenges and opportunities of using big data analytics in an agricultural value chain |
Analytical study |
NA |
65 |
-Studying data ownership rules in an agriculture supply chain |
-Developing access to technology infrastructure for rural areas |
Dubey et al., 2019)/Management Decision |
Studying how to use big data analytics to improve the agility of a supply chain |
Statistical analysis / Hypotheses tests |
Collected data from 173 experts by questionnaire |
46 |
-Using other theoretical perspectives to study the effect of big data analytics on the agility of a supply chain |
-Using case-based methods instead of survey-based research |
Dubey et al. (2018b)/The International Journal of Logistics Management |
Studying big data predictive analytics’ impact on coordination and visibility in humanitarian supply chains |
Least squares regression / Hypothesis tests |
Survey responses from 205 International Non-Government Organizations |
26 |
-Considering country culture and/or supply base complexity in a predictive model |
-Applying agent-based simulation methods |
Irani et al. (2018)/Computers & Operations Research |
Studying organizational factors that impact the amount of waste in a food supply chain |
Fuzzy cognitive map / Simulation |
Data from surveying 34 stakeholders in food industry in Qatar |
21 |
-Use Delphi method to involve a wider set of participants |
-Develop the same approach in countries besides Qatar |
Jeble et al. (2018)/The International Journal of Logistics Management |
Studying the impact of big data and predictive analytics on sustainable business development |
Resource-based view logic / Contingency theory |
Survey data from 205 individuals in auto components industry |
40 |
-Studying the actual impact of big data and predictive analytics on a business firm rather than just the perception of the impact |
-Explore data that can be more generalized |
Lai et al. (2018)/The International Journal of Logistics Management |
Studying the factors that determine the adoption of big data analytics in supply chains |
Technology-organization-environment (TOE) framework |
Survey data from 210 Chinese IT managers and business analysts |
28 |
-Increase the environmental safety of big data |
-Studying the other factors that may affect the adoption of big data analytics, such as supply chain scale and delivery complexity |
Lau et al. (2018)/Production and Operations Management |
Using consumer social media comments for sales forecasting |
Parallel sentiment analysis / Machine learning |
Consumer comments datasets in English and Chinese |
31 |
-Combining parallel topic models with lifelong learning strategies |
-Examining parallel ensemble models for better sales forecasting |
Gupta et al. (2019b)/Technological Forecasting and Social Change |
Using big data analytics to support data-driven decision making in circular economical supply chains |
Stakeholder perspective on circular economy |
Interview data from 10 expert employees |
19 |
-Using larger empirical data for this study |
-Studying inter-organizational relationships, intra-organizational dynamics, and informational privacy issues in supply chains |
Lamba & Singh (2019)/Technological Forecasting and Social Change |
Using big data analytics to study a supplier’s selection and lot-sizing problem under carbon cap-and-trade regulations |
Mixed integer non-linear program |
Experimental problem sets |
15 |
-Developing heuristics that can obtain the solution via a faster method |
-Studying the same model’s behavior under various carbon emission regulations |
Lamba et al. (2019)/Computers & Industrial Engineering |
Studying a supplier selection and lot-sizing problem in dynamic supply chains |
Mixed integer non-linear program |
A randomly generated dataset |
23 |
-Studying the stochastic demand with the same problem settings |
-Focusing on the veracity and value characteristics of big data |
Shen et al. (2019)/Technological Forecasting and Social Change |
Using big data analytics to find if a retailer must sell green or non-green products first, according to shelf space limitations |
Bayesian analysis |
NA |
19 |
-Studying incentive contracts in order to achieve a coordinated supply chain |
-Studying the role of government interventions on selling green products |
-Studying this case with enough shelf space for both green and non-green products |
Singh & El-Kassar (2019)/Journal of Cleaner Production |
Studying the impact of the integration of big data with green supply chain management and human resource management on a firms’ sustainability |
Statistical analysis / Hypotheses testing |
Survey data from 215 employees in Saudi Arabia, the United Arab Emirates, Egypt, and Lebanon |
40 |
-Using the same research framework of this study with multisource and/or multi-time datasets |
-Using mixed methods instead of quantitative data within the same research framework |
Yu et al. (2019)/International Journal of Forecasting |
Using Google trends to forecast the oil consumption in an oil supply chain |
Cointegration tests / Granger causality analysis |
Data from Google trends |
38 |
-Considering the dynamic between Google trends and oil consumption over time |
-Introducing other types of big data, such as social networks, to the proposed model |