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The purpose of this paper is to examine the strategic response to Industry 4.0 for Chinese automotive industry and to identify the critical factors for its successful implementation.

A technological, organizational, and environmental framework is used to build the structural models, and statistical tools are used to validate the model. The data analysis helps to determine which factors have impact on the strategic response and whether their relationships are positive or negative. Interpretive structural modeling method is applied to further analyze these derived factors for depicting the relationship.

The result shows that company size and nature do not increase the use of advanced production technologies, while other factors have positive impacts on improving the technology adoption among the companies surveyed.

A strategic response to Industry 4.0 not only helps in improving organizational competitiveness, but it also has social and economic implications. For this purpose, empirical data are collected to measure the understanding of Industry 4.0 in the Chinese automotive industry.

Despite the fact that the Chinese Government has proposed the “Made in China 2025” approach as a way to promote smart manufacturing, little empirical evidence exists in the literature validating company’s perspective toward Industry 4.0. This paper is to fill the research gap.

The purpose of this paper is to examine the potential impacts of various variables on product return activities after online shopping. Previous studies on customer behaviour have been predominantly concerned with return on used products and other product-quality-related constructs in the model. This study aims to specially examine the logistics service-related and customer intention–related variables for general products under the e-commerce circumstance.

Structured questionnaire data for this study were collected in the two southeast cities of China (162 useable responses). Structural equation modelling was used to examine the latent variables.

The results confirmed that product return intention has the greatest impact on online shopping returns with a direct effect of 0.63, followed by the flexibility in return (logistics service) with a direct effect of 0.49.

Such a model not only enriches the theoretical understanding of customer behaviour studies but also offers online shopping stores and platforms a quantitative benchmark and new perspective on the design of online shopping supply chains by considering product returns so as to improve the customer satisfaction.

With the new generation Industry 4.0 coming, as well as globalization and outsourcing, products are fabricated by different parties in the distributed manufacturing network and enterprises face the challenge of consistent planning of semi-finished product in each manufacturing process in different geographical locations. The purpose of this paper is to propose a real-time operation planning system in the distributed manufacturing network to intelligently control/plan the manufacturing networks.

The feature of the proposed system is to model and simulate large distributed manufacturing networks to streamline the mechanical and production engineering processes with radio frequency identification (RFID) technology, which can keep track of process variants. To deal with concurrency and synchronization, the hierarchical timed colored Petri net (HTCPN) formalism for modeling is selected in this study. This method can help to model graphically and test the discrete events of concurrent operations. Fuzzy inference system can help for knowledge representation, so as to provide knowledge-based decision assistance in distributed manufacturing environment.

In this proposed system, there are two main sub-systems: one is the real-time modeling system, and the other one is intelligent operation planning system. These two systems are not parallel in the whole systems while the intelligent operation planning system should be embedded in any stage of the real-time modeling system as needed. That means real time modeling system provides the holistic structure of the studied distributed manufacturing system and realize real-time data transfer and information exchange. At the same time the embedded intelligent operation planning system fulfill operation plan function.

This new intelligent real-time operation system realizes real-time modeling with RFID-based HTCPN and smart fuzzy engine to fulfill intelligent operation planning which is highly desirable in the environment of Industry 4.0. The new intelligent manufacturing architecture will highly reduce the traditional planning workload and improve the planning results without manual error interference. The new system has been applied in a practical case to demonstrate its feasibility.

The purpose of this paper is to propose an adjusted approximate regenerative model (ARM) for a constant‐work‐in‐process (CONWIP)‐based production system that solves the problem of deciding the number of intermediate bulk container in a pharmaceutical company to hold the work in process.

The problem was modeled as a CONWIP system and the ARM was adjusted to estimate the throughput.

By comparing the results from the original ARM and adjusted ARM, a clear superiority of the proposed method is shown for the real case. In addition, the robustness of the adjusted ARM is demonstrated in terms of the violation of rigid assumption and the impacts brought by the limitation of buffer space before the bottleneck station.

The novelty of the proposed model is to take the long transportation time between machines into consideration.

The purpose of this paper is to present an integrative approach for the problem of service capacity design for the ground crew at the airport check-in counters.

Using data collected from the airport check-in counters, several characteristics of the service demand were studied. First, many service time-dependent operating characteristics are addressed over a specified time window to evaluate the problems from the current ground crew allocation. Second, a linear programming model is developed to determine the optimal number of check-in counters to open over the specified time window based on the case study. In addition, sensitive analysis is conducted to further explore the dependency effect of the factors as well as improve the model. Third, the shift adjustment of the ground crew allocation is provided so as to satisfy the given service demand.

Numerical results indicated the effectiveness in the improvement of the human resource utilization of the proposed approach. The superiority of performance is illustrated in terms of less counters to be opened and decreased daily working hours.

The study is novel by applying the integrated approach so as to design a proper service capacity and thus the service supply and demand can be balanced.

The purpose of this paper is to formulate procurement strategies and determine the optimal procurement quantity in order to maximize profit through forward contracting and the spot market.

The procurement process is modeled at various stages along a time horizon from the perspective of the buyer, with consideration of uncertain yields, stochastic demand and dynamic spot market prices. Monte Carlo simulation based experiments were conducted to figure out the best procurement quantity for five different scenarios. The framework was developed to understand the impact of different uncertain variables on a firm's profit. A case study was carried out in a steel making company in India, with real data.

The results indicate that the proposed approach enables buyers to achieve higher profits under volatile demand conditions. In the case study, it was found that the profit is higher for the spot market than for contract pricing if there is significant demand and spot price volatility.

This research considers not only demand uncertainty but also supply uncertainty in the procurement process, and profit analysis was carried out to enable an enterprise to set up a procurement plan by using forward contracting and the spot market. This study should also increase awareness in both academia and industry on the opportunities of using the spot market to enhance flexibility and to mitigate risk in the procurement process.

The purpose of this paper is to apply a multi-criteria decision-making (MCDM) framework to evaluate distribution strategies for an e-tailer. An application of MCDM method, the hybrid DANP–VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model, is used for e-tailers’ distribution strategy evaluation. The choice of distribution strategies under various dimensions is evaluated.

The authors used a hybrid MCDM model to solve the decision-making framework, which combines Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based analytic network process and VIKOR method. Data were collected from the experts (e-tail manager, logistics manager, operations manager and distribution center (DC) manager) using two questionnaires, first for the influential relationship among the criteria and dimensions and second for a performance rating of each alternative (distribution strategies) against each criterion.

DANP with VIKOR method prioritizes the distribution strategies in the following order: DC shipment, drop shipment, click and collect, store shipment and click and reserve. Performance gap was calculated based on the VIKOR method to provide distribution strategies to an e-tailer under different situations. The authors infer that in developing country, product characteristics and transportation have a major influence on deciding the distribution strategy.

Decision-making framework will provide e-tail mangers a knowledge-based understanding to select the distribution strategy under the different situations related to the performance, product, e-tailer and external characteristics for smooth order fulfillment process. The insights developed by this research provide a framework for rational decision making in distribution strategy selection in e-business.

This is the first kind of a study which offers a decision framework for e-tail managers on how to choose distribution strategies under different situations which are related to the performance, product, e-tailer and external characteristics.

The invention and use of mobile commerce (m-commerce) technology have progressed in recent years. In small to medium-sized enterprises (SMEs), the decision to implement business-to-business m-commerce is a multiple-criteria decision analysis problem that involves both qualitative and quantitative factors, and its evaluation may be based on imprecise information or uncertain data. Furthermore, there may be significant dependences or important feedback among different levels of criteria or alternatives. However, most conventional decision models cannot capture these complex interrelationships. The purpose of this paper is to adopt a new hybrid multiple attribute decision model (MADM) model to evaluate the implementation of business-to-business m-commerce by SMEs in Taiwan to enhance the thinking of management and improve decision gaps.

In this study, the authors present the use of a new hybrid MADM combined with a decision-making trial and evaluation laboratory (DEMATEL) method to construct an influential network relationship map (INRM) and find the influential weights of DANP (DEMATEL-based ANP) in criteria from the influential relationship matrix, and the modified VIKOR method using influential weights to evaluate and integrate the criteria performance in the gaps and to analyze how to reduce the gaps to evaluate the decision to implement business-to-business m-commerce by SMEs based on INRM.

The findings of using the new hybrid MADM model can efficiently and successfully be applied to the business-to-business m-commerce of SMEs to improve and reduce the performance gaps among each criterion/aspect when setting improvement strategies for achieving an aspiration level based on INRM.

This study achieves the following: successfully building a decision network (called an influential network relation map (INRM)) of the technological advances and implementations of business-to-business m-commerce for solving the inter-dependence and feedback of criteria/aspects in the real world problem; how changing effective solutions from existing performance of situations/alternatives into aspiration levels to fit the current competitive markets in the business-to-business m-commerce of SMEs; and efficiently shifting from ranking and selection when determining the most preferable approaches to performance improvement by modified VIKOR methods.

Knowledge management seeks collaborative practices among organisations to generate technical, adapt and share knowledge to obtain a sustainable competitive advantage in cross-border business activities. This paper aims to disentangle the crucial determinants of knowledge management in inter-organisational arrangements settings.

In the first stage, after an in-depth literature review, the main knowledge management drivers are identified. In the second stage, based on the identified drivers, the importance and relationship between the drivers are evaluated by expert opinions from academic and executive activists. Eventually, in the last stage, a multi-layer decision-making approach has been proposed and used to determine the relationship and the importance of the drivers.

The findings of this paper assess the ranking of the different elements from experts’ opinions and discuss important theoretical and managerial implications. The influential factors were identified through an extensive literature review, which combined with the views of experts from academia and industry (international firms). Furthermore, the ranking of factors based on the experts’ overall opinion was used to discuss theoretical and managerial contributions.

This research provides a better understanding of the interrelationships between the key drivers of knowledge management, which helps management draw more effective strategies to address the cultural differences between firms. Moreover, understanding of the importance of the systems and structures that define the nature of the collaboration in inter-organisational settings, as well as the risks related to those are presented in this research.

The purpose of this research article is to investigate the critical risk factors associated with the digitalization impact on the Indian construction industry, as these firm plans to implement digitalization in order to improve their construction management processes.

In this research article, risk factors and dimensions are taken from diverse industries and validated in the construction domain by industry and academic experts. Further, multi-criteria decision-making techniques are employed to assess the Indian construction sector scenario quantitatively. The interrelationship and weightage of risk factors and dimensions are determined by the Fuzzy Decision-making Trial and Evaluation Laboratory Analytic Network Process (DANP) method. However, the method Grey Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS) is used to determine the ranking of each risk factor.

This study finds 14 critical risk factors along with four risk dimensions. Operational and financial dimensions are significant risk dimensions. Whereas the threat of high outlay and low yield is a significant risk factor in construction. Besides that, the interrelationship among risk factors, the weightage of each factor and the ranking of critical risk factors are also identified.

This research article uses Fuzzy DANP and Grey TOPSIS techniques as exploratory research methods with a limited group of construction professionals from a leading Indian construction firm. Furthermore, comprehensive confirmatory research can also be performed with a large group of construction experts using advanced analytical techniques to validate the ranking of critical risk factors.

The findings of this study provide insight into the knowledge of construction firms by emphasizing significant risk factors related to digitalization in construction operations. Another finding of this study shows that the risks associated with digitalization in construction are similar to those in manufacturing, where high outlay and low yield hold a significant role in the transformation process.

The research is unique since there have only been limited studies in the Indian construction scenario to analyze the significant risks associated with digitalization. Furthermore, this study demonstrates that the combination of Fuzzy DANP and Grey TOPSIS techniques may be used successfully to prioritize risks in construction digitalization, which is still in its early phases.