3. Big data in supply chain management (other than manufacturing and logistics)

3.6. Marketing and sales

Big data analytics can help inform marketing managers of current trends in product sales beyond simply the demand forecasts. For example, product reviews can be approved more easily to help influence sales performance in many studies. The impact of big data analytics on improving sales forecasting was studied in an analytical review by Boone et al.. Sagaert et al. shows that using big data analytics can improve the transparency of market dynamics to sales managers. Using big data analytics in the case study of a tire company could improve forecasting accuracy by 16.1% over the traditional method. Moreover, Li et al. showed that managing a demand chain with big data and electronic commerce works much better than traditional methods of supply chain management.

Using product-in-use data has been proven to reduce the uncertainty for aftermarket (spare parts) demand planning. Gawankar et al. studied the impact of new technologies - such as the Internet of Things and big data analytics - on the retail environment in India. They found that the retailing industry in India is eager to use new technologies in the retailing environment that they call "Retail 4.0" in their study. Big data analytics was also used by Liu & Yi to show the correlation between the price and the products' environment friendliness degree. It shows that the available data can used for targeted advertisements in a supply chain's green environment. Another study in big data pricing application was done by Liu, in which he considered the data company to be an echelon in the supply chain, and determined its benefits using the Stackelberg game.

Analyzing social media data can help supply chains increase their number of customers in the system through personalized services. Companies can analyze social networks, mobile, and web data to track the way that a customer wants to use the product. On the other hand, Aloysius et al. survey of a group of retail store customers showed that many people have concerns about how much of their personal information is collected, which can negatively affect the store's image.

Some of the selected journal articles regarding big data applications in supply chain management are summarized in Table 2.

Table 2 High-quality articles using big data in supply chain management practices. 

Author / Journal

Contribution

Study approach

Case study (NA stands for Not Applicable)

Future research topic(s) in the article

Hazen et al./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

-Developing new methods for controlling data

Chen et al./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

-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./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

-Testing the contributed approach on other supply chains to determine its general applicability

-Simplifying the contributed mathematical approach

Giannakis & Louis/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

-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./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

-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./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

-Developing unbiased managerial guidance for using big data analytics in supply chain management

Gunasekaran et al./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

-Investigating top managers' commitment towards developing big data predictive analytics capabilities

Kache & Seuring/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

-Studying the constituents of a big data ecosystem as keys for optimal supply chain productivity

Roßmann et al./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

-Interviewing other fields' experts

-Studying the impact of potential technological applications on social dynamics in supply chain management

Choi/Transportation Research Part E

Studying the impact of social media comments on quick response supply chains in fashion

Analytical mathematical modeling / Newsvendor model

NA

-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./Applied Economic Perspectives and Policy

Studying the challenges and opportunities of using big data analytics in an agricultural value chain

Analytical study

NA

-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

-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./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

-Considering country culture and/or supply base complexity in a predictive model

-Applying agent-based simulation methods

Irani et al./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

-Use Delphi method to involve a wider set of participants

-Develop the same approach in countries besides Qatar

Jeble et al./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

-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./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

-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./Production and Operations Management

Using consumer social media comments for sales forecasting

Parallel sentiment analysis / Machine learning

Consumer comments datasets in English and Chinese

-Combining parallel topic models with lifelong learning strategies

-Examining parallel ensemble models for better sales forecasting

Gupta et al./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

-Using larger empirical data for this study

-Studying inter-organizational relationships, intra-organizational dynamics, and informational privacy issues in supply chains

Lamba & Singh/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

-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./Computers & Industrial Engineering

Studying a supplier selection and lot-sizing problem in dynamic supply chains

Mixed integer non-linear program

A randomly generated dataset

-Studying the stochastic demand with the same problem settings

-Focusing on the veracity and value characteristics of big data

Shen et al./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

-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/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

-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./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

-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