Data envelopment analysis (DEA) is popularly used to evaluate relative efficiency among public or private firms. Most DEA models are established by individually maximizing each firm's efficiency according to its advantageous expectation by a ratio. Some scholars have pointed out the interesting relationship between the multiobjective linear programming (MOLP) problem and the DEA problem. They also introduced the common weight approach to DEA based on MOLP. This paper proposes a new linear programming problem for computing the efficiency of a decision-making unit (DMU). The proposed model differs from traditional and existing multiobjective DEA models in that its objective function is the difference between inputs and outputs instead of the outputs/inputs ratio. Then an MOLP problem, based on the introduced linear programming problem, is formulated for the computation of common weights for all DMUs. To be precise, the modified Chebychev distance and the ideal point of MOLP are used to generate common weights. The dual problem of this model is also investigated. Finally, this study presents an actual case study analysing R&D efficiency of 10 TFT-LCD companies in Taiwan to illustrate this new approach. Our model demonstrates better performance than the traditional DEA model as well as some of the most important existing multiobjective DEA models.

This study aims to investigate the potential transformation of small and medium enterprises (SMEs) in Taiwan, China, to meet the United Nations (UN) sustainable development goals (SDGs) by adopting Industry 4.0. Taiwan is performing excellently at the core of Industry 4.0, information technology competence; however, we are curious if the competence required is available and acquainted by SMEs for achieving SDGs. As the consulting staff of the government, we hypothesized that adopting Industry 4.0 would lead to the success of sustainability. The analytical methodology is the model of technology, organization, and environment (TOE). We conducted the questionnaire survey to test if the adoption of Industry 4.0 will guarantee the success of sustainability. A systemic approach is employed to develop and parametrize the final model between adopting Industry 4.0 and sustainability, using structural equation modeling (SEM). Finally, we found a significant gap for Taiwanese SMEs to achieve sustainability via Industry 4.0 because only three hypotheses are supported: organizational resource availability influences Industry 4.0 adoption, investment costs impact sustainability, and external support pushes the adoption of Industry 4.0. We propose some possible solutions for the government to help SMEs reach the achievement of SDGs.