List of Forthcoming Journals

The journals in the list below have been accepted for publication in Operations and Supply Chain Management: An International Journal. We are currently in the process of assigning each of these entries into our upcoming issue. Once published, you can access the corresponding article for free through our repository. Please feel free to contact us via Contact Us page or our email for any inquiries.

1. The Influence of Supply Chain Process Integration on Firm Performance

Yaw Agyabeng-Mensah (Dalian Maritime University, China),
Esther Nana Konadu Ahenkorah (Regent University College of Science and Technology, Ghana)

Today’s competitive business environment has caused firms to abandon the use of traditional ways of improving performances. This has resulted in the search for many drivers of performance by both academicians and practitioners. This study examines the impact of supply chain management information systems on supply chain process integration and tests both individual and collaborative effects of supply chain process integration, customer satisfaction, and competitive advantage on the performance of firms. A survey was conducted using 275 supply chain and logistics managers who work in small and medium enterprises in Ghana. The data is collected using structured questionnaires. The explicit relationships between supply chain management information systems, supply chain process integration, customer satisfaction, competitive advantage and firm performance are proven using smartpls 3.2.8. The results suggests that the supply chain management information systems positively and significantly influences supply chain process integration. Again, the findings suggest that supply chain process integration, competitive advantage and customer satisfaction combine to significantly influence performance of firms. This is an indication that supply chain process integration instantaneously creates both customer satisfaction and competitive advantage, which reflects in the firm performances.

2. Data Analytics in the Supply Chain Management: Review of Machine Learning Applications in Demand Forecasting

Ammar (Aamer),
Luh Putu Eka (Eka Yani),
I Made Alan (Priyatna)

In today’s fast-paced global economy coupled with the availability of mobile internet and social networks, several business models have been disrupted. This disruption brings with it a whole list of opportunities and challenges for organizations and the domain of supply chain management. Given the availability of big data, data analytics is needed to convert data into meaningful information which plays an important role in supply chain management. One of the disruptive data analytics techniques which are predicted to impact growth, employment, and inequality in the market is automation of knowledge work, or better known as machine learning. In this paper, we focused on comprehensively overviewing machine learning applications in demand forecasting and underlying its potential role in improving the supply chain efficiency. A total of 1870 papers were retrieved from Scopus and Web of Science databases based on our string query related to machine learning. A reduced total of 79 papers focusing on demand forecasting were comprehensively reviewed and used for the analysis in this study. The result showed that neural network, artificial neural network, support vector regression, and support vector machine were among the most widely used algorithms in demand forecasting with 27%, 22%, 18%, and 10% respectively. This accounted for 77% of the total reviewed articles. Most of the machine learning application (65%) was applied in the industry sector and a limited number of articles (5%) discussed the agriculture sector. The practical implication of this paper is in exposing the current machine learning issues in the industry to help stakeholders and decision-makers better plan transformation actions.

3. Understanding the Interrelationship Between Culture of Quality, Employee and Organizational Performance

Vikas Kumar (University of the West of England, Bristol, UK ),
Yu Han (University of Warwick, Coventry, UK ),
Ngân Tuy?t Tr??ng (RMIT University Vietnam, Ho Chi Minh City, Vietnam),
Nhu Y Ngoc Hoang (University of Economics Ho Chi Minh City, Vietnam),
Arvind Upadhyay (University of Brighton, Brighton, UK )

Culture of Quality (COQ) is regarded as an important component of total quality management (TQM) however this is a relatively new emerging theme, compared to other concepts in the quality management domain. As a result, literature resources on this topic are relatively scarce and there is a lack of empirical validation of the COQ framework. This study therefore attempts to fill this research gap and aims to empirically investigate the dimensions of the COQ and their impact on organisational and employee performance. The study also explores the interrelationship between each dimension of COQ. A set of hypotheses are proposed and empirically tested based on the 120 survey responses mostly from the Asian region. The survey data was analysed using SPSS through descriptive analysis, reliability analysis, correlation analysis and regression analysis. Findings show that COQ dimensions; leadership emphasis, message credibility, peer involvement and employee ownership encourage better employee performance. The study further suggests that organisations should work on ensuring supervision from top to bottom, accelerating information flow, creating autonomous working environment and getting staff involved in strategic management. In addition, findings show that COQ factors also interact with each other in varying degrees. The study therefore addresses an important research gap by empirically investigating the COQ dimensions and suggesting that from an employee perspective, organizational performance can be accelerated through quality culture management.

4. Three-echelon Green Supply Chain Inventory Decision for Imperfect Quality Deteriorating Items

Yosef Daryanto (Universitas Atma Jaya Yogyakarta, Indonesia),
Hui Ming Wee (Chung Yuan Christian University, Taiwan)

This paper presents an integrated supply chain inventory model for deteriorating items with an imperfect quality considering its environmental impact, particularly the supply chain carbon footprint. An imperfect production system produces a certain number of defective items. Therefore, in our model, the manufacturer conducts a 100% quality check to prevent the delivery of defective items. A third-party logistics (3PL) company supports the logistics between the manufacturer and the buyer, by transporting the products from the manufacturer to a warehouse and then delivering the products in a smaller quantity to the buyer. The proposed solution procedure determines the number of deliveries per cycle, delivery interval, and delivery quantity between the 3PL and the buyer simultaneously. It also determines the production quantity of the manufacturer and the delivery quantity from the manufacturer to the 3PL. The objective is to minimize the expected total cost and to reduce total carbon emissions.

5. Requirements for Blockchain Technology in Supply Chain Management: An Exploratory Case Study

Ari Sivula (Seinäjoki University of Applied Sciences, Seinäjoki, Finland),
Ahm Shamsuzzoha (University of Vaasa, Vaasa, Finland),
Petri Helo (University of Vaasa, Vaasa, Finland)

The aim of this research study is to look for possible research opportunities to applying block-chain technology in supply chain management and logistics. In addition, accompanying chal-lenges to utilizing blockchain in supply chain management along with possible solutions are also provided. To fulfil the study objective, both theoretical and empirical approaches are adopted for this study. With respect to theoretical approach, relevant literature on blockchain was reviewed considering both technical and economic aspects, its architecture and implemen-tation challenges. The empirical part of the research was conducted by studying three case companies operating in the domains of wood construction, consulting and regional develop-ment, and technology. Three case companies were analysed with respect to the application of blockchain in their supply chain operations. From the study outcomes, it was noticed that blockchain technology can be utilized successfully in supply chain management in various business domains in order to provide extended customer value, transparency and enhanced ser-vice network.

6. A Humanitarian Logistics-based Planning for Rescue and Relief Operation After a Devastating Fire Accident

Kanchan Das (East Carolina University, Greenville, NC 27858, USA),
Reza S. Lashkari (University of Windsor, Windsor, ON N9B 3P4, Canada),
Azizur R. Khan (Vision & Method: Research, Training and Consulting Service, Dhaka, Bangladesh)

The frequency of fire disasters is fortunately low, but planning the logistics and related routings for rescue, relief, and rehabilitations operations are major issues in launching any humanitarian assistance. In addition to the logistics planning issues, the reasons for the occurrence of the fire disasters should also be determined so that measures may be put in place to prevent future disasters as well as any potential consequences that may occur after the fire is extinguished. Most cities have efficient fire departments quipped with resources and fire brigades to initiate immediate measures to control the fire and to start the rescue operation. Moreover, most governments take steps to provide relief and rehabilitation assistance to the affected population. Rescue, relief, and rehabilitation steps in traffic-congested cities, especially in heavily populated areas with many businesses and markets, are highly challenging. This research proposes a mathematical modeling-based approach for planning the transportation of relief and rescue resources; conducting relief and rescue operations; and outlining measures to prevent future recurrences. The model will be illustrated using the chemical explosion-fed fire which occurred on February 20, 2019 in the old part of Dhaka in Bangladesh.


Qian Huang ( Waseda University, Tokyo, Japan),
Shunichi Ohmori ( Waseda University, Tokyo, Japan),
Kazuho Yoshimoto ( Waseda University, Tokyo, Japan)

This study develops a global production–shipping planning model that incorporates a decision on transportation mode after considering the cost function of different transportation modes from the shipper’s point of view. We propose tramp shipping, liner shipping, and a mixed mode to select the optimal shipping mode, considering transshipment and consolidation to exploit economies of scale under a given network. We present mathematical formulations of tramp, liner and mixed modes and apply a piecewise approximation technique with mixed-linear integer programming to linearly approximate the concave minimization problem and efficiently solve it using an off-the-shelf solver. In order to verify the effectiveness of the proposed modes, the three modes are compared and discussed in numerical examples. The advantages and disadvantage of the three modes are discussed under different situations. The result is a decision aided system to support production–shipping planning in selecting the optimal transportation mode.


Blanka Tundys (University of Szczecin, Poland),
Tomasz Wi?niewski (University of Szczecin, Poland)

The considerations undertaken concern the green supply chain for organic products. The authors present the development of the market for such products and the latest trends in world markets in connection with the creation and implementation of a new business strategy - relating to the implementation of environmental aspects. The aim of the discussion is to indicate the theoretical basis for the construction of the green supply chain, with particular emphasis on the specificity of organic products. Theoretical considerations are accompanied by the results of empirical research, which indicate in which areas and in the scope of implementation of which management tools there are significant differences between enterprises and what may be the reasons for this. The novelty and value of considerations consist in the reference to the principles and elements of the green chain to ecological products and the indication why a holistic approach to environmental protection should be promoted (i.e. production and the whole supply chain promoting the principles of sustainable development). The analysis of literature, methods of descriptive and mathematical statistics and ANOVA (analysis of variance) were used in the considerations.

9. A multi-objective modeling approach for integrated manufacturing and preventive maintenance planning

Kamran S. Moghaddam (Clayton State University, USA)

This research studies the effects of preventive maintenance and replacement activities on operational costs, overall reliability, and availability of a multi-tasking manufacturing machine. A multi-objective optimization model to find Pareto-optimal preventive maintenance and replacement schedules for a repairable multi-component machine with increasing failure rate is developed. The planning horizon is divided into equally-sized periods in which minimal repairs, full replacement, or do-nothing actions can be performed on each machine’s component. The machine reliability for preventive maintenance aspects, its availability for production purposes, and total operational costs for both preventive maintenance and manufacturing planning are formulated as the objective functions and the multi-objective model is solved using a simulation-based optimization algorithm in real case study. It is shown that the developed mathematical models and the solution method can effectively generate Pareto-optimal preventive maintenance schedules that can be integrated into aggregate production plans.

10. A Hybrid Forecasting Technique to Deal with Heteroskedastic Demand in a Supply Chain

Sanjita Jaipuria (Indian Institute of Management Shillong, India),
S.S. Mahapatra (National Institute of Technology Rourkela 769008 India)

Under uncertain environment, maintaining a proper safety stock is very important to cope with the stock-out situation. Improper estimation of safety stock quantity leads to an improper estimation of the order resulting in causes of bullwhip effect and net-stock amplification. In practice, demand is heteroskedastic in nature i.e. the variance of the demand varies with time. Therefore, it is important to predict the changing demand variance to update safety stock level in each replenishment cycle. The Autoregressive Integrated Moving Average (ARIMA) model applied to predict the mean demand assumes homoscedasticity of data. However, Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model can effectively deal with heteroskedastic demand and help in projecting the changing demand variance. Hence, a combined approach of ARIMA and GARCH (ARIMA-GARCH) model has been proposed in this work to evaluate the safety stock level and order quantity. The performance of ARIMA and ARIMA-GARCH has been evaluated considering the demand from a cement manufacturing company. The demand of cement exhibits seasonal in pattern and highly fluctuating. Using cement demand data, ARIMA (2, 1, 1) (0, 1, 1)12 and GARCH (2, 1) model is identified to forecast 12-months ahead mean and variance of demand to determine the safety stock and order quantity in each replenishment cycle applying the equations proposed by Zhang (2004) and Luong & Phien (2007). Further, bullwhip effect and net-stock amplification ratio are estimated to evaluate the performance of ARIMA-GARCH model against the ARIMA model. From the study, it has found that ARIMA-GARCH model outperforms the ARIMA as it updates the safety stock to calculate order quantity in each replenishment cycle.

11. An empirical investigation of the relationship between store attributes and customer satisfaction: A retail operations perspective

Yash Daultani (ndian Institute of Management Lucknow, India),
Kshitij Goyal (Kalicharan Darshanlal Jewellers, Birla Jewels Limited, Gwalior - 474006, India),
Saurabh Pratap (Indian Institute of Information Technology, Design and Manufacturing, Jabalpur - 482005, India)

The purpose of this study is to identify key retail store attributes that impact customer satisfaction. The conceptual model is developed with the help of extant literature and expert opinion. The study analyzes the relationship among the store attributes, customer satisfaction, advocacy, and repurchase intention to provide operational insights to retail store managers concerning key store attributes. In particular, jewellery stores in India are selected for this research investigation. The data from jewellery stores and customers located in the Gwalior district is collected using the convenience sampling. The partial least squares-structural equation modeling (PLS-SEM) method is used for model validation and data analysis. The results reveal that the store-related attributes, product-related attributes, and service quality-related attributes have a positive influence over customer satisfaction. In these three attribute categories, the most sought factors by consumers were store layout & ambience, product durability, and overall assistance, respectively. Further, the customer satisfaction is found to affect advocacy and repurchase intention. The study suggests that jewellery store managers should focus on managing the select store attributes identified in this study to improve customer satisfaction, advocacy, and repurchase intentions. Though the study is conducted in the context of Indian jewellery stores, the insights are equally useful and explorable in other retail stores situated at diverse locations.

12. Blockchain and Supply Chain Management: A New Paradigm for Supply Chain Integration and Collaboration

Michael Wang (Auckland University of Technology, Auckland, New Zealand ),
Yong Wu (Griffith University, Brisbane, Australia),
Bruce Chen (Monash University, Melbourne, Australia ),
Melissa Evans (Scion (The New Zealand Forest Research Institute), Rotorua, New Zealand)

Despite there are some arguments about blockchain, it has been highlighted as an important distributed secure technology in the 21st century. It is an incorruptible digital ledger of economic transactions that can be programmed to record not just financial transactions but virtually everything of value. Dobrovnik et al. (2018) suggest that blockchain is a revolutionising technology that would change industries at an international level, add values to firms and supply chain networks, improve commerce, and drive economy. Although blockchain has attracted attentions, very few blockchain studies have been focussed on supply chain integration and collaboration areas. This study illustrates the possibilities of applying blockchain technology in the coordination of activities for effective and efficient supply chain management. The study takes a closer look at the use of blockchain in supply chains beyond cryptocurrency, payment, and finance via the use of smart contract and consensus algorithm (i.e. imposing constraints). The key attributes of blockchain are discussed and potential questions were identified in New Zealand. The expected outcome of this study will advance the understanding of the blockchain and supply chain literature, besides inspire both researchers and practitioners to consider the use of blockchain in different context-aware future studies.

13. A Supply Chain Selection Method for Early-Stage Companies based on an adapted Quality Function Deployment optimization approach

Omar Romero-Hernández (Hult International Business School and University of California, Berkeley, USA),
Sergio Romero (Instituto Tecnologico Autonomo de Mexico, Mexico),
MV Shivaani (Hult International Business School, San Francisco, USA)

In this paper, the QFD methodology is adapted to accommodate the assessment and selection of supply chain configurations. This new methodology incorporates a series of factors including supply chain needs, technical specifications, relationships among specifications, and potential synergies. Resultantly, the original contribution of this methodology is the selection of a supply chain scenario that balances the desire to fulfill a series of needs, along with the ability of a supply chain to deliver according to specification. This balance between need fulfilment and availability of supply chain is particularly difficult to strive for early-stage companies. Accordingly, this methodology was applied into the analysis and selection of four different supply chain scenarios considered for the production and final delivery of a large number of customer orders, placed for the Tesla Roadster vehicle, which needed to be fulfilled in record time. In all cases, scenarios were placed in context of the company’s mission so that business goals and operating decisions were aligned. The application was successful, and a specific supply chain design scenario was selected. The proposed methodology could be a roadmap for designing incipient supply chains.

14. IoT in Supply Chain Management: Opportunities and Challenges for Businesses in Early Industry 4.0 Context

Tharaka de Vass (Victoria University Business School, Victoria University, Australia),
Himanshu Shee (Victoria University Business School, Victoria University, Australia),
Shah J. Miah (Victoria University Business School, Victoria University, Australia)

The Internet of Things (IoT) is a global network of smart devices that integrate physical world with digital world. While the IoT is reported to be a foundation technology for the emerging Industry 4.0 era, empirical evidence of IoT use in supply chain management is scant. This study, therefore, investigates the opportunities and challenges of IoT use in the retail supply chains using grounded theory based interviews with managers from the Australian retail industry. The content analysis using NVivo reveals that IoT deployment improves visibility of goods movement, data capture, partner communication, and business intelligence. However, retailers face challenges due to the lack of top management initiative, new technology acquisition cost, stakeholders' reluctance to accept change, unwillingness to share data, and inadequate interoperability of software systems. The study offers a proof-of-concept of IoT benefits that strengthen the IoT-related investment decision, sheds light on adoption challenges and develops propositions for future research.

15. An Investigation of Factors Impacting Lean Implementation in the Indonesian Fast-Moving Consumer Goods Industry

Florence ng (National University of Singapore, Singapore),
John Aik Joo Heng (PSB Academy Pte Ltd, Singapore),

The fast-moving consumer goods (FMCG) industry is promising in Indonesia with recorded sales of more than USD 10 billion, which represents more than 18% of Indonesia’s gross domestic product in 2016. Despite the lucrative market, FMCG companies face challenges due to intense competition and increasing operational costs. Consequently, Indonesian companies have begun to explore lean implementation to decrease their costs and improve efficiency, but with scarce success. This study investigates the critical success factors of lean implementation in the Indonesian FMCG industry, as such implementation cannot optimally occur if the implementing company does not successfully manage the important factors that affect lean implementation. This study tested various factors—namely, organizational culture, personnel capability, communication, and leadership and management involvement—that impact lean implementation and organizational performance in Indonesia’s FMCG industry. It was also found that leadership and management involvement are the most important factors. Based on the obtained results, this research also proposes recommendations regarding the best lean implementation practices in Indonesian FMCG companies.