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Recent research has highlighted the beneficial role of supply chain resilience for ensuring efficient production and business processes. The purpose of this study is to explore enablers of supply chain resilience. In particular, the authors examine whether and how dynamic capabilities and knowledge management can help firms develop a resilient supply chain in times of high disruption and uncertainty.

A single longitudinal case study design was adopted. Data was collected over 8 years from a Pakistani textile producer and supplier through semi-structured interviews and was analyzed through NVivo to generate codes and themes that contributed to the development of the supply chain resilience model.

The analysis of case study shows that our focal firm strategically acquired, transferred and integrated market knowledge by investing in digital technologies and idiosyncratic resources and consequently developed a supply chain model that was resilient in addressing logistics and delivery challenges in uncertain & critical times.

The study brings together three main research streams of organizational theory, namely supply chain, knowledge management and dynamic capabilities, and proposes a nuanced resilient supply chain model.

By applying the research findings, managers can adjust, develop and adopt supply chain resilience to address market volatilities, thereby creating value and longevity in their supply chain operations. However, the findings are context specific and should be applied cautiously.

The outcomes provide early hints on how companies in emerging economies can adopt and integrate novel digital technologies, and overhaul their organizational routines to facilitate knowledge management and develop dynamic capabilities, and consequently enhance the resilience of their supply chain operations.

This paper aims to investigate the influences of process parameters on part quality, electrical energy consumption. Moreover, the relationship between part quality and energy consumption of UTR9000 photosensitive resin fabricated by stereolithography apparatus (SLA) was also assessed.

Main effect plots and contour maps were used to analyze the interactions and effects of various parameters on energy consumption and part quality, respectively. Then, a growth rate was used defined as the percentage of the value of energy consumption (or the part quality) of the sample compared to the minimum value of the energy consumption (or the same part quality), to jointly analyze relationships between part quality and energy consumption on a specific process parameter.

The part qualities can be improved with increased energy consumption via adjusting layer thickness, without further increasing energy consumption through adjusting laser power, over-cure and scanning distance. Energy consumption can be highly saved while slightly decreasing the tensile strength by increasing layer thickness from 0.09 mm to 0.12 mm. Energy consumption and surface roughness can be decreased when setting laser power near 290 mW. Setting an appropriate over-cure of about 0.23 mm will improve tensile strength and dimensional accuracy with a little bit more energy consumption. The tensile strength increases nearby 5% at a scanning distance of 0.07 mm compared to that at a scanning distance of 0.1 mm while the energy consumption only increases by 1%.

In this research, energy consumption and multiple part quality for SLA are jointly analyzed first to accelerate the development of sustainable additive manufacturing. This can be used to assist designers to achieve energy-effective fabrication in the process design stage.

The purpose of this paper is to investigate the reasons for implementing enterprise resource planning (ERP) systems in Australia and the issues encountered during the course of implementation.

A questionnaire survey is conducted, research frame is selected from the Australian manufacturing sector and a final list of 350 Australian manufacturing companies was prepared from which 79 responses were received, representing a response rate of 23 per cent.

The paper finds that the planned and actual use of ERP systems is pervasive in the Australian manufacturing sector, with both small and large companies implementing or planning to implement an ERP system. It was also revealed that ERP system implementation benefits are concentrated more in quickly providing high‐quality information within firm.

Respondents are limited to Australian companies, and results may be regional in nature. Further study is suggested to benchmark the result of this research to other countries.

Provide insights on ERP implementation at least to the Australian companies and hopefully to companies in other countries.

Supply chain management has become such a popular topic in modern business management and researches. It brings the revolutionary philosophy and approach to manage the business with the sustained competitiveness. However, the existing performance measurement theory fails to provide its necessary support in strategy development, decision making, and performance improvement. This paper attempts to propose an innovative performance measurement method to contribute to the development of supply chain management. A process‐based systematic perspective is employed to build an effective model to measure the holistic performance of complex supply chains. Fuzzy set theory is introduced to address the real situation in judgment and evaluation processes. The main framework of this method is outlined with some suggestions and a simple example.

Facing uncertain demand and supply, customers and suppliers are encouraged to make their supply chain more flexible and adaptive to the environment. The primary objective of this paper is to gain an understanding of the issues surrounding flexibility and adaptability in supply chain management from an industrial practitioner.

A semi‐structured interview and follow up interviews were conducted with a logistics manager of a renowned international company.

The study supports that the aforementioned characteristics, flexibility and adaptability, are useful in practical supply chain applications. Some practical advice is also reported.

This paper bridges the gap between academic theoretical studies and the expectations from an industrial practitioner regarding flexibility and adaptability in supply chain management. A similar study could be extended to more industrial practitioners in order to collect more useful opinions from them.

The purpose of this paper is to test the effectiveness of fuzzy time series (FTS) forecasting system in a supply chain experiencing disruptions and also to examine the changes in performance as the authors move across different tiers.

A discrete event simulation based on the popular beer game model is used for these tests. A popular ordering management system is used to emulate the behavior of the system when the game is played with human players.

FTS is tested against some other well-known forecasting systems and it proves to be the best of the lot. It is also shown that it is better to go for higher order FTS for higher tiers, to match auto regressive integrated moving average.

This study fills an important research gap by proving that FTS forecasting system is the best for a supply chain during disruption scenarios. This is important because the forecasting performance deteriorates significantly and the effect is more pronounced in the upstream tiers because of bullwhip effect.

Having a system which works best in all scenarios and also across the tiers in a chain simplifies things for the practitioners. The costs related to acquiring and training comes down significantly.

This study contributes by suggesting a forecasting system which works best for all the tiers and also for every scenario tested and simultaneously significantly improves on the previous studies available in this area.

Whether or not a company is able to compete in the local and global arena depends significantly on how effectively the company can build up the partnership synergy with their business counterparts. With the emergence of a dispersed manufacturing network, the important issue is the criteria for the selection of the right partners for the right tasks. In this respect, it is essential to develop the necessary techniques to measure the performance of potential business partners prior to making the decision of partner selection. This paper suggests a performance measurement technique incorporated with on‐line analytical processing (OLAP) technology to support enterprise decisions related to selecting appropriate business partners. It also includes examples to illustrate how to apply this technique in real industrial situations.

The purpose of this paper is to empirically test a framework which identifies the relationships between supply chain management (SCM) practices, operational performance and innovation performance of Malaysian manufacturing and service firms.

Data for the study were collected from a sample of 163 Malaysian manufacturing and service firms. The research model was tested using structural equation modeling.

The results show that SCM practices in both the upstream and downstream supply chain have a direct and significant impact on organizational and innovation performance of Malaysian firms. Innovation improvement caused by SCM also results in better organizational performance. The findings also reveal that manufacturing and service firms in Malaysia do not have a significant difference in their SCM practices.

The time sequence of the association between the variables could not be concluded given that cross‐sectional data were used. This study also focuse only on Malaysian firms.

This paper shows the importance of SCM practices and how they directly influence organizational and innovation performance. This result will be encouraging to firms in other developing countries. This paper has developed and validated a multi‐dimensional construct of SCM practices, and this tool can assist decision makers of Malaysian firms to evaluate the efficiency of their current SCM practices.

The paper presents one of the few studies which empirically validates the relationships between SCM practices and organizational and innovation performances. The study also focuses on a developing country which is in transition from being manufacturing focused to service focused.

To develop a performance measurement system (PMS) in the application of supplier relationship management operated under a supply chain benchmarking framework. Acting as a monitoring tool for evaluating the performance of maintenance logistics providers against the defined performance levels stated in the contract, and facilitating the application of benchmarking approach in maintenance logistics activities.

A six tiers collaborative management model is designed in building the PMS, by which information sharing of performance history of suppliers is made possible. By following the work flow of the PMS, performance of suppliers is benchmarked with the best‐in‐class supplier, resulting in the identification of the most appropriate supplier for the particular requirement.

PMS helps a company and its suppliers to understand the performance gap between its service levels with the best‐in‐class practice. The resulting performance gap provides valuable information in the formulating of a new supply chain and strategic plan in solving problems and challenges in aviation industry. By means of PMS, a company can make decisions with the basis of a good relationship with its business partners, especially in the maintenance logistics area.

The design of PMS must take into consideration of the data sources, the duration of taking the required data, and the focal point on collecting information. Moreover, findings from the study have to be revised every two years.

By applying PMS in one of the leading airlines in Hong Kong, suppliers' deficiencies in the logistics performance are identified easily. Moreover, current operational service level is effectively enhanced and the combination of the best‐in‐class supplier service package is accurately selected.

Computer simulation techniques are used to evaluate the performance of a welding assembly line which requires modification to achieve some of the philosophies of a just‐in‐time manufacturing environment. The simulation of the existing line using GPSS/H confirmed the operational problems which had been previously identified, and allowed the validation of the computer model. The computer model was then altered to evaluate the performance of several alternative modified assembly lines which would avoid the present operational problems. Discusses some of the techniques used to develop these models, their simulation using the GPSS/H simulation language, and the benefits of using simulation in analysing manufacturing processes.