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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.

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.

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.

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.

This study develops an integrated zero waste discharge planning approach for improving resource efficiency in a pulp-and-paper manufacturing firm.

The objectives of this study are to (1) identify the environmental, technical and social metrics in resource efficiency; (2) utilize fuzzy multi-objective programming and the hybrid particle swarm optimization algorithm to solve the fuzzy problem; and (3) develop an assessment for resource efficiency improvement in an industrial case study.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

The findings demonstrate the superiority of hybrid particle swarm optimization algorithm in generating optimal results for a pulp-and-paper manufacturing firm.

Resource efficiency is a multi-objective problem in an uncertain environment. In particular, zero waste discharge planning involves minimizing the total cost and maximizing the waste material recovery rate, wastewater reuse, and waste heat recovery.

The purpose of this paper is to propose a cradle-to-cradle (C2C) zero discharge production planning system with a fuzzy hybrid optimization model that uses fuzzy comprehensive evaluation to establish fuzzy indicators, and then defuzzify the fuzzy indicators to construct a fuzzy multiobjective programming (FMOP) model.

The FMOP model pursues overall satisfaction using a particle swarm optimization algorithm to produce the best output values for the maximum waste paper recovery rate, the condensate reuse quality and minimum total cost of the zero discharge production planning system.

Recovered waste heat is seldom recycled and consumed in Taiwan. There is a need to capture and utilize heat recovery and use it in the production process supply. In contrast, waste materials are used as resources to perform waste paper recovery and recycle the waste heat of evaporation collection in the production process.

This paper develops a system to establish the best output value for an overall high satisfaction level. According to the results, the waste paper recovery rate is 99.8 percent, condensate reuse quality water is 102.6 tons and the total cost of the zero discharge production planning system is NT$1,312,012.

The purpose of this paper is to analyze the wastewater discharge and a zero-wastewater-discharge (ZWD) reproduction plan is designed for a paper mill in Taiwan.

The proposed model of ZWD reproduction planning is established using the fuzzy comprehensive evaluation and Taguchi method to determine the overall wastewater recovery rate. Still the prior studies failed to address a systematic approach to optimize the waste water recovery rate.

The optimal solution for clean water is 500 tons, recovery electrodialysis reversal is 345 tons, the wastewater reuse performance is 1.3 and waste heat recycling performance is 0.8, the larger number is performed well. The results shows that the maximum overall waste water recovery rate is 97.8 percent.

A paper mill is strived for improving their sustainable development. In real situation, there is a need to address the qualitative information and qualitative data to carry out the optimal ZWD reproduction planning.

The purpose of this paper is to develop an integrated approach for a green product cradle-to-cradle (C2C) fuzzy recycling production planning model.

This paper applies the failure mode and effects analysis technique and Taguchi experimental design method, develops a green product C2C performance evaluation system that considers the fuzzy impacts of environmental laws and regulations, green goodwill, and environmental efficiency of targeting countries, and decides both the optimal green production plan and estimated optimal life cycles.

This study compares the different degree of maturity in environmental regulations, and various recycling situations are simulated to demonstrate the successful applicability of the proposed model as well as the incentive policy for Taiwan, the USA and Bangladesh.

Previous studies failed both to develop a holistic recycling production plan which is able to consider both the optimal combination of recycled components used and final green products produced with the maximum total resultant sales profit and to consider the potential failure phenomenon of recycled components adopted in the final product. Furthermore, most prior studies ignored the influence of environmental law, goodwill of the product and the efficiency of recycling mechanism of the community.

Construction and demolition waste (CDW) continuously causes environmental and social problems. These formidable challenges lead to sustainable issues and are an increasingly urgent issue worldwide. Prior studies have neglected to link the triple bottom line (TBL) to a reliable estimation or empirical model for estimating CDW production performance and lack empirical sensitivity analysis in profit maximization. This study proposes an attribute analysis to build a cost–benefit analysis (CBA) to obtain profit maximization.

This study uses fuzzy set theory to develop a cost and benefit analysis (CBA) model to assess the sensitivity analysis in terms of its performance on addressing the environmental, economic and social aspects. The model is used to weigh the sum of benefits such as financial gain and total costs of actions taken to mitigate the negative impacts.

Based on the sensitivity analysis conducted, the environmental, economic and social mean scales were significantly changed, i.e. increased, and profits increased drastically. The results provide an insight into environmental legislation compliance, environmental investment and environmental impact as the cause attributes for the CDW recycling profit increase. The results prove that sensitivity analysis is viable to infer that a sustainable production performance can achieve more revenue and profit through an adequate selection of attributes regarding the TBL aspects to address the firm's uncertainty problem in multiple criteria analysis.

This study builds a CBA model to maximize profits for recycled CDW material by linking of environmental, economic and societal aspects for recycled CDW assessments. It considers a sustainability structure with criteria based on TBL aspects to assess production performance to realize the Sustainable Development Goals and presents fuzzy set theory and sensitivity analysis to solve the uncertainty problem in the construction industry.

This study aims to construct a valid hierarchical sustainable human resource management (SHRM) model with interrelationships among its attributes in terms of qualitative information.

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.

This study finds that green performance management and compensation lead to human resource benefits and economic sustainability in the HRM model.

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.

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.

Population aging was a global trend, and the most obvious thing after aging was the change in skin appearance. Therefore, the active ingredients that delay skin aging were particularly noticed. Past studies had pointed out that Chinese herbal extracts can improve skin elasticity, reduce wrinkles and melanin precipitation. The purpose of this paper is to explore whether combining hydrolyzed collagen with Chinese herbal extracts can improve skin conditions and achieve anti-inflammatory effects.

Fifty subjects were randomly divided into collagen or placebo groups, and one bottle of collagen or placebo drink was used every day for four weeks, after which skin and inflammatory factors were tested.

In comparison with the baseline results, the skin parameters were improving after four-week intervention. In addition, the IL-6, IL-8, TNF-a were significantly decreased and tissue inhibitor matrix metalloproteinase 1 (TIMP-1) was increased after four-week hydrolyzed collagen intervention.

This study showed that hydrolyzed collagen combined with Chinese herbal extracts can improve the condition of the skin, and can also reduce inflammatory associated factors, thereby achieving anti-aging effects.

This paper aims to propose an integrative and result-driven health-care knowledge management (HKM) model and discuss the findings of a research that examines how the KM initiatives of a major private Brazilian hospital system are linked to its health-care performance outcomes.

Data were collected from a top-level Brazilian private hospital system (Mater Dei Healthcare System – MDHS), which is composed of three large hospitals internationally accredited by ISO 9001/2000, NIAHO and JCI. Multiple qualitative approaches were used to collect data such as 16 in-depth interviews with health professionals and managers, document analysis, participatory observation and benchmarking interviews with two reference hospital networks in Brazil.

The proposed health-oriented KM model is an expansion of the organizational knowing cycle model (Choo, 1996), adding absorptive capacity (ACAP) as a new construct. The paper discusses how ACAP integrates with sense-making, knowledge creation and decision-making processes within the health-care context. Information technology and clinical governance were identified as support factors to the HKM processes.

The paper presents a pragmatic and result-driven knowledge management (KM) model using health-care-welfare key performance indicators, as well as the emergence of KM as an integrative and strategic approach to hospital management.

The present study presents a knowledge-based perspective to clinical staff management, demonstrating the tangible results of KM initiatives that contribute to health and management performance outcomes.

This study aims to explain why e‐mails trigger emotional response states in receivers and to explore the influence of e‐mail formats on the receivers' intention to forward e‐mails.

Data were collected from 305 undergraduate and EMBA students in one university in Northern Taiwan. Participants were asked to fill out the questionnaire based on any forwarded e‐mail that they had recently received.

This study reveals that people will have a stronger intention to forward e‐mails that make them feel positive emotions, display richer information, are greater in length, or include audio and visual information.

This study shows that e‐mail forwarding function maintains guanxi with others, supporting the social psychology theory that personal emotional states will trigger specific behaviors. Also, this paper extends the explanation of the “information richness” theory concerning the influence of format on receivers' e‐mail forwarding intentions.

This study can assist marketing managers in developing e‐commerce by exploiting the special features of e‐mails identified in the study.

This study provides a behavioral model of the type of e‐mails most likely to be forwarded. Enterprises can use this model in developing better guanxi with their customers.