**1. Introduction**

With the development of globalization, the establishment of a stable supply chain has become one of the important strategies for the sustained development of an enterprise. However, sometimes, due to the catastrophic economic or political fluctuations, some county or region will lose its original advantages, forcing companies to transfer their supply chain to other countries to reduce the possible risk. Faced with these types of disruptive challenges, companies need to respond rapidly and in a timely manner to retain their competitive advantages. How to transfer the original supply chain and select the best alternatives are critical decisions for managers. In the past, it has been suggested that production processes and supply chains can be adjusted to respond with decentralized production [1–4]. Some researchers believe that relocating the supply chain can strengthen an enterprise's competitive advantage [5,6]. Many studies have confirmed that the choice of production line is one of the most important strategic decisions for corporate development, directly affecting the costs and benefits of corporate operations [7–9]. The choice of supply chain also plays a very important role in building a company's competitive advantage and ensuring its sustainable development. The relocation of production lines plays a key in sustainable supply chain management in today's competitive markets.

In prior research on manufacturing, considerations for location selection include economies and markets, government and governance, business efficiency, infrastructure, human capital and education in the evaluation framework [7,9–11]. However, few studies have incorporated the concepts of sustainability and innovation as criteria in the evaluation system or systematically discussed the entire evaluation framework. Wang et al. [12] pointed out that environmental regulations will certainly have an impact on some locations and will have different effects on different types of industries. Mudambi et al. [13] found that site selection decisions are related to creative activities and the resources required to carry these out, which can create new assets and lay the ground work for a competitive advantage. Therefore, it is necessary to include the dimensions of sustainability and innovation in the study of location selection.

Many studies have used statistical models to explore the issues of location selection. For example, Ye et al. [14] surveyed 3558 new foreign manufacturing enterprises in China's Pearl River Delta and found that the heterogeneity of the enterprise interacts with location selection. Zheng and Shi [15] found that industrial land supply and allocation policies interact with corporate site selection. Industrial land allocation policies have positive effects on corporate site selection. On the other hand, multiple criteria decision making (MCDM) models have already been used to explore the issue of location selection. For example, Liu [6] used a fuzzy Delphi method combined with a Decision Making Trial and Evaluation Laboratory (DEMATEL) method to evaluate the choice of investment location and output an impact diagram. Marinkovi´c et al. [11] used the two round Delphi method to confirm decision indicators combined with an Analytic Hierarchy Process (AHP) method to facilitate location selection for new sectors in the Information and Communication Technology (ICT) industry. Although qualitative or quantitative methods have been used in many studies to confirm the relationship between the factors or criteria, the applied models often overlook the interdependency between criteria [12,14–17]. The DANP-mV (DEMATEL-based ANP- modified VIKOR) model is very appropriate for handling the problem of interdependency and easy to operate compared with the original DANP model [18]. However, decisions on location selection, due to the complexity and interaction of the evaluation criteria, often involve lead to a dilemma between rationality and sensitivity. Chang and Lin [19] pointed out that location selection is usually based solely on the subjective preferences of senior managers, so decisions are normally biased. To avoid the subjective weight problem of the DANP-mV model, this study incorporates the entropy method to obtain objective weights for inclusion in the model. Then, the modified VIKOR (VIšekriterijumsko Kompromisno Rangiranje) method is applied to select the optimal alternatives for the relocation of a production line [20–23]. Finally, an empirical analysis by implementing the proposed DANP-mV model is conducted onto an electronic product manufacturer that is suffering from the impact of international economics and trade. The company's supply chain has a global layout and has 175 service spots. The company has a goal of being sustainability. For this vision, this study focuses on the relocation of manufacturing plants for the sustainable development.

The contribution of this study is that the method should help managers to evaluate possible locations, solving the problem through a comprehensive and scientific process, so the results can be closer to reality. The following improvements are made:


The rest of the paper is organized as follows—a systematic review of the research on location selection problems is given in Section 2. The revised DANP-mV model is introduced in Section 3. An empirical example is illustrated in Section 4 and the results and management implications are presented in Section 5. Finally, Section 6 provides the findings and future research directions.
