Yuh-Jiuan Parng, Taufik Kurrahman, Chih-Cheng Chen, Ming Lang Tseng, Hiền Minh Hà and Chun-Wei Lin
This study aims to construct a valid hierarchical sustainable human resource management (SHRM) model with interrelationships among its attributes in terms of qualitative…
Abstract
Purpose
This study aims to construct a valid hierarchical sustainable human resource management (SHRM) model with interrelationships among its attributes in terms of qualitative information.
Design/methodology/approach
This study applies the fuzzy Delphi method to validate SHRM attributes and visualize the causal interrelationships among these attributes using a fuzzy decision-making trial and evaluation laboratory method.
Findings
This study finds that green performance management and compensation lead to human resource benefits and economic sustainability in the HRM model.
Practical implications
Open environmental communication, green human resource planning, green training and development, employee eco-friendly behavior and organizational culture are the top five criteria supporting practical improvement in the healthcare industry.
Originality/value
The emergence of new, unprepared, and inexperienced health care entities with inadequate human resource management (HRM) potentially causing social problems within the industry, SHRM is necessary to balance the social, environment, and economic performance and must be studied by both academicians and practitioners. However, the HRM application field is still in its infancy, which limits the understanding of its potential.
Details
Keywords
Chun-Wei R. Lin, Yuh-Jiuan Melody Parng and Yu-Lin Chen
Responding to natural resource depletion and carbon dioxide (CO2) emission problems, and also the stricter government’s energy regulations, the purpose of this paper is to develop…
Abstract
Purpose
Responding to natural resource depletion and carbon dioxide (CO2) emission problems, and also the stricter government’s energy regulations, the purpose of this paper is to develop a sustainable waste heat recovery optimal-profit-oriented management model especially targeting on the easily forgotten low- and medium-temperature waste heat in the industry. In the paper, a system is constructed to facilitate converting the low- and medium-grade waste heat in factories into electricity, and yields optimal profit.
Design/methodology/approach
This paper integrates an efficient Organic Rankine Cycle (ORC) system from both sustainable energy reservation and cost effectiveness approaches with an optimization model that adopts particle swarm optimization (PSO) algorithm to determine proper installation locations and feasible generator sets. The system is constructed to facilitate converting the low- and medium-grade waste heat in factories into electricity, and yields optimal profit. The model considers the environmental factors: temperature, heat amount, equipment configuration of the number of ORC sets, and detailed investment cost constraints.
Findings
The results show that annual investment return rate, annual increase in electricity, power generation efficiency, and annual CO2 emission reduction are all highly improved, and investment recovery period is shortened. Also, the larger scale of the waste heat emission, the better the performance is achieved. Finally, the study also completes a sensitivity test under dynamic conditions of electricity price, generator sales price and factory budget constraints, and the results are consistently robust. More valuably, this paper demonstrates applications on two different manufacturing industries with various waste heat emission scales to prove the accountability.
Originality/value
The main contributions are in three aspects. First, it proves that applying PSO to a nonlinear mathematical model can help determine the optimal number and style configuration of generators for waste heat sources. Second, different from the prior research works focusing on power generation, this paper also deliberates the cost factors, cost of generators, costs of numerous peripheral components and future maintenance costs to ensure the factories not conflict with the financial limitations. Third, it is not only successfully applied in two industries with different scales, but also robust with various economic tests, electricity price change, generator sales price change, and investment budget adjustments.