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The purpose of this paper is to investigate the effects of extrinsic motivation, workplace learning, employer trust and self-efficacy on foreign laborers’ cross-cultural adjustment.

This paper uses structural equation modeling to analyze the data from a sample of 258 Vietnamese laborers in Taiwan.

The results show a significantly positive impact of extrinsic motivation, workplace learning, employer trust and self-efficacy on cross-cultural adjustment.

The findings of this study provide important implications for academic researchers and organizations concerning management and development of successful foreign laborers. From a theoretical aspect, this study shows new evidence on the impacts of extrinsic motivation, workplace learning, employer trust and self-efficacy on foreign laborer cross-cultural adjustment. In addition, this study enriches theories in the field of self-determination motivation, workplace learning, trust and self-efficacy literature. From a practical aspect, this study provides implications for business managers to make better policies in training and managing foreign laborers.

Establishing a performance‐oriented evaluation in public sectors is the key to successful administrations. However, because of lacking relative comparable measuring standards, it is difficult to measure the relative performance of one unit while comparing to other units with regard to the multiple criteria decision making (MCDM) of performance evaluation. This paper aims to focus on the performance ranking of research and development (R&D) projects in Taiwan's public sectors.

The algorithm in this paper is based on the concept of fuzzy set theory and the hierarchical structure analysis. The analyzing method adopts the methods of standard normal distribution, linear transformation, and fuzzy MCDM, carrying on the analysis of multiple criteria of the performance evaluation.

This paper constructs linguistic values to the subjective judgments and analyzes the ranking results of the performance evaluation with respect to 45 R&D projects of one of Taiwan's electric power companies. Thus, the paper demonstrates a successful way of evaluating R&D projects in the public sector.

In this paper, a decision algorithm based on the fuzzy set theory is proposed to solve the performance evaluation of R&D projects in public sectors. In order to solve the difficulties of measuring one unit of the relative performance of quantitative criteria comparing to the other units, the method of standard normal distribution is adopted while measuring the quantitative criteria. The concept of linguistic values and fuzzy numbers are used in this paper since they could easily be used to describe the subjective measurement of the appropriateness of alternatives and the importance weightings of criteria.

This paper aims to propose a new method for evaluating the quality and prioritizing of the human resources (HRs) based on trust, reputation, agility, expertise and cost criteria in the expert cloud. To evaluate some quality control (QC) factors, a model based on the SERVQUAL is used.

The aim of this paper is to offer a fast and simple method for selecting the HRs by the customers. To achieve this goal, the ranking diagram of different HRs based on the different criteria of QC is provided. By means of this method, the customer can rapidly decide on the selection of the required HRs. By using the proposed method, the scores for various criteria are evaluated. These criteria are used in the ranking of each HR which is obtained based on the evaluation conducted by previous customers and their colleagues. First, customers were asked to select their needed criteria and then by constructing a hierarchical structure, the ranking diagram of different HRs is achieved. Using a ranking system based on evaluating the quality of the model, satisfy the customer needs to be based on the properties of HRs. Also, an analytical hierarchical process-based ranking mechanism is proposed to solve the problem of assigning weights to features for considering the interdependence between them to rank the HRs in the expert cloud.

The obtained results showed the applicability of the radar graph using a case study and also numerically obtained results showed that a hierarchical structure increases the quality and speed rating of HR ranking than the previous works.

The suggested ranking method in this paper allows the optimal selection due to the special needs of any given customer in the expert cloud.