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The purpose of this paper is to propose a methodology to analyze a large amount of unstructured textual data into categories of business environmental analysis frameworks.

This paper uses machine learning to classify a vast amount of unstructured textual data by category of business environmental analysis framework. Generally, it is difficult to produce high quality and massive training data for machine-learning-based system in terms of cost. Semi-supervised learning techniques are used to improve the classification performance. Additionally, the lack of feature problem that traditional classification systems have suffered is resolved by applying semantic features by utilizing word embedding, a new technique in text mining.

The proposed methodology can be used for various business environmental analyses and the system is fully automated in both the training and classifying phases. Semi-supervised learning can solve the problems with insufficient training data. The proposed semantic features can be helpful for improving traditional classification systems.

This paper focuses on classifying sentences that contain the information of business environmental analysis in large amount of documents. However, the proposed methodology has a limitation on the advanced analyses which can directly help managers establish strategies, since it does not summarize the environmental variables that are implied in the classified sentences. Using the advanced summarization and recommendation techniques could extract the environmental variables among the sentences, and they can assist managers to establish effective strategies.

The feature selection technique developed in this paper has not been used in traditional systems for business and industry, so that the whole process can be fully automated. It also demonstrates practicality so that it can be applied to various business environmental analysis frameworks. In addition, the system is more economical than traditional systems because of semi-supervised learning, and can resolve the lack of feature problem that traditional systems suffer. This work is valuable for analyzing environmental factors and establishing strategies for companies.

A systems perspective of waste management allows an integrated approach not only to the five basic functional elements of waste management itself (generation, reduction, collection, recycling, disposal), but to the problems arising at the interfaces with the management of energy, nature conservation, environmental protection, economic factors like unemployment and productivity, etc. This monograph separately describes present practices and the problems to be solved in each of the functional areas of waste management and at the important interfaces. Strategies for more efficient control are then proposed from a systems perspective. Systematic and objective means of solving problems become possible leading to optimal management and a positive contribution to economic development, not least through resource conservation. India is the particular context within which waste generation and management are discussed. In considering waste disposal techniques, special attention is given to sewage and radioactive wastes.

This paper aims to propose a method for the longitudinal analysis of the environment considering both firms' and environmental variables.

The study is based on a sample of firms in Canary Islands (Spain) for 2000 and 2003. Managerial perceptions are considered, based on the cognitive perspective. The measurements used are the result of applying the Rasch model and the rack and stack analyses. This approach provides information about how dynamic the firms perceive the environment and also about how the items are perceived.

The results show that most firms perceive that dynamism increased between 2000 and 2003. From the perspective of the environmental variables, the most dynamic are perceived to be competition, demand, consumer motivation and technological resources.

This paper proposes a longitudinal method for environmental scanning that include both firms' and environmental variables. It considers managerial perceptions, that is the information entering the decision making process. It is one of the first papers to study environmental scanning with Rasch model and one of the few about longitudinal environmental analyses. It opens a field of research and applications of the Rasch model in the management literature.

The objective of this life cycle environmental cost analysis (LCECA) model is to include eco‐costs into the total cost of the products. Eco‐costs are both the direct and indirect costs of the environmental impacts caused by the product in its entire life cycle. Subsequently, this LCECA model identifies the feasible alternatives for cost‐effective, eco‐friendly parts/products. This attempts to incorporate costing into the life cycle assessment (LCA) practice. Ultimately, it aims to reduce the total cost with the help of green or eco‐friendly alternatives in all the stages of the life cycle of any product. The new category of eco‐costs of the cost breakdown structure includes eight eco‐costs, namely cost of effluent/waste treatment, cost of effluent/waste control, cost of waste disposal, cost of implementation of environmental management systems, costs of eco‐taxes, costs of rehabilitation (in case of environmental accidents), cost savings of renewable energy utilization, and cost savings of recycling and reuse strategies. Development of a suitable cost model and the identification of the feasible alternatives are performed simultaneously. Various checklists based on multiple environmental criteria will be used to ensure the eco‐friendly nature of the alternatives. On the basis of the calculated environmental impact indices (EII), priorities will be made for the selection of suitable alternatives. The mathematical model of LCECA aims to define the relationships between the total cost of products and the various eco‐costs concerned with the life cycle of the products, and determine quantitative expressions between the above‐said costs. A computational LCECA model has been developed to compare the eco‐costs of the alternatives. This model will include a break‐even analysis to evaluate the alternatives, and sensitivity analysis and risk analysis modules. This model aims at a cost‐effective, eco‐friendly product as an end result. This LCECA model will be compatible with the existing LCA software tools.

Pro-environmental behaviour (PEB) has always been one of the most critical topics in academia and industry. The primary goal of this study is to identify the current research progress and developmental trends of PEB by doing an exhaustive analysis of the existing literature. The study also aims to streamline the future research possibilities in PEB with the current research interests.

A total of 209 published articles from 1993 to 2021 were collected from the Scopus database and analysed using an integrated approach of bibliometric analysis, network analysis, and content analysis techniques. The bibliometric analysis was performed with the help of statistical program “R,” and further analysis was carried out using Gephi and VOS viewer software.

The systematic mapping of this field gives an exhaustive review of the available literature by identifying annual publication growth, most contributing authors, journals, emerging keywords, and themes. Sustainability was found to be the most contributing journal, and Paille was the topmost contributing author. The keywords such as corporate social responsibility, organizational citizenship behaviour towards the environment (OCBE), and green human resource management (HRM) were recently identified as the emerging niche in the literature. The content analysis findings give a robust roadmap for further research in this area.

This study enriches the literature on workplace pro-environmental behaviour by presenting a detailed, systematic, and exhaustive review of the existing publications using a combination of research methodology.

This paper reports the results of an exploratory study of inter‐coder reliability of annual report social and environmental disclosures content analysis. Using the sentence‐based coding instruments and decision rules from Hackston and Milne (1996), this study reports the co‐agreement levels reached by three coders over five rounds of testing 49 annual reports. The study also provides a commentary on the implications of formal reliability analysis for past and future social and environmental disclosures content analyses, and the complexities of formal reliability measurement. The overall findings suggest that the coded output from inexperienced coders using the Hackston and Milne approach with little or no prior training can be relied on for aggregate total disclosures analysis. For more detailed sub‐category analysis, however, the findings suggest a period of training for the less experienced coders with at least 20 reports appears necessary before their coded output could be relied on.

The purpose of this study is to better understand the nexus between environmental taxes and other environmental management systems (EMSs) and to propose an alternative framework for implementing environmental protection tax (EPT) in China.

The study uses a multimethod approach encompassing document analysis and comparative analysis. The archival data covers laws, reports, regulations, guidelines and standards related to the EPT and EMS sub-systems in China.

The study identifies several institutional features of environmental taxes that have not been fully explored in past tax research. In addition, the study reveals that information-sharing mechanisms are key to addressing the risks and uncertainties associated with the implementation of an environmental tax and that the mechanisms are grounded in the nexus among EPT and two EMS sub-systems.

The findings of this study have implications for the understanding of China’s environmental tax system, the Environmental Impact Assessment system and the pollutants discharge permit (PDP) system. The construction of an alternative framework provides insights for approaches to environmental taxation. A limitation of this study is that the application of the framework might be undermined by the inaccurate manual sampling, as some pollutants may be non-replicable.

The findings of this study are relevant to policymakers who are designing, improving or abandoning environmental taxes for alternate solutions to environmental issues.

The insights gained from this study may be of assistance to lower the risks and uncertainties associated with the implementation of an environmental tax.

The study contributes to approaches to environmental taxes by constructing an alternative framework that connects an environmental tax system with two EMSs. The framework lays the groundwork for some promising research opportunities. Additionally, the study extends the tax accounting literature (Hanlon and Heitzman, 2010) by connecting accounting and environmental knowledge and developing a transdisciplinary approach. The study also contributes to the emerging body of literature that addresses the challenges in implementing environmental taxes in China.

The purpose of this paper is to present a method for the environmental impact analysis of machine-tool cutting, which enables the detailed analysis of inventory data on resource consumption and waste emissions, as well as the quantitative evaluation of environmental impact.

The proposed environmental impact analysis method is based on the life cycle assessment (LCA) methodology. In this method, the system boundary of the cutting unit is first defined, and inventory data on energy and material consumptions are analyzed. Subsequently, through classification, five important environmental impact categories are proposed, namely, primary energy demand, global warming potential, acidification potential, eutrophication potential and photochemical ozone creation potential. Finally, the environmental impact results are obtained through characterization and normalization.

This method is applied on a case study involving a machine-tool turning unit. Results show that primary energy demand and global warming potential exert the serious environmental impact in the turning unit. Suggestions for improving the environmental performance of the machine-tool turning are proposed.

The environmental impact analysis method is applicable to different machine tools and cutting-unit processes. Moreover, it can guide and support the development of green manufacturing by machinery manufacturers.