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Green supplier selection is one of the crucial activities in green supply chain management. However, limited studies have addressed the vagueness and complexities during the selection process, particularly in multi-criterion decision-making (MCDM) circumstances. Hence, the purpose of this paper is to develop a group decision model using a modified fuzzy MCDM approach for green supplier selection under a complex situation.

The proposed study develops a framework for sorting decisions in green supplier selection by using the hesitant fuzzy qualitative flexible multiple attributes method (QUALIFLEX). The synthetic consistent or inconsistent indexes were used to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix.

The proposed framework has been successfully applied and illustrated in the case example of CB02 contract section in Hong Kong–Zhuhai–Macau Bridge project. The results show various complicated decision-making scenarios can be addressed through the proposed approach. The synthetic (in)consistent indexes are able to calculate all alternative suppliers by normalizing the hesitant fuzzy decision matrix.

The research contributes to improving accuracy and reliability decision-making processes for green supplier selection, especially under vagueness and complex situations in megaprojects.

Housing infrastructure is the basic need for people of a community and due to disaster many houses may severaly damaged. Stakeholders and decision makers should focus on this issue and make the infrastructure more resilient against natural hazards. As dependency plays a very important role in resilience, it is important to study the dependencies and correlations among the housing infrastructure resilience factors. The evaluation of dependencies involve vagueness due to subjective judgement of experts.

In this work, the interaction between the housing infrastructure resilience factors are evaluated by using two different approaches such as crisp DEMATEL (Decision-Making and Trial Evaluation Laboratory) and rough DEMATEL (intregated crisp DEMATEL and rough set theory), where rough theory addressed the involvement of vagueness. These two approaches are compared with each other to find the effectiveness of rough DEMATEL over crisp DEMATEL.

The important factors of housing infrastructure resilience are identified by using both the approaches against flood hazard.

The limitation of rough DEMATEL method is that it does not differentiate the type of influence such as positive or negative.

The outcome of the work will helps the stakeholders and ecission makers to make the infrastructure more resilient.

This study identify the imporatnat resilience factors of housing infrastructure against flood hazard by using two methodologies.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this chapter is to demonstrate that, despite the extensive literature on firm-specific advantages (FSAs) and country-specific advantages (CSAs) produced since Rugman’s classic matrix (1981), little progress has been made in empirically operationalizing the second concept.

Through a review of the international business (IB) literature that refers to the CSA concept, we identify the “vagueness” in the usage of this concept. First, we present a concise literature review of the CSA construct, with a link to the “double diamond” theoretical model of Rugman and D’Cruz (1993) and Rugman and Verbeke (1993). Second, we present the results of the bibliographic analysis on the use of the construct by a variety of authors.

We demonstrate the weak conceptual grounding of the CSA concept by reviewing the literature on host-CSAs attracting Chinese overseas foreign direct investment (OFDI). Apart from the fact that various authors use different sources of data, an important reason for contradictory results is the fact that each author tests host-CSA through different indicators. Here, we propose a list of variables and indicators based on the “double diamond” model and test these empirically.

IB researchers should start conducting serious studies on home-CSAs and host-CSAs instrumental to attracting investments, defining clear indicators and using replicable data based on publicly available information. This chapter is the first to show that the concepts developed by Rugman (1981) and expanded by Rugman, A. M. and Verbeke, A. (2008) (Internalization theory and its impact on the field of international business. Research in Global Strategic Management, 14, 155–174) are relevant to advance in the quantitative operationalization of concepts within IB theory.

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.

In this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.

This research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.

The proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.

The proposed model is generic and can be applied for large-scale GSC environments with little modifications.

No prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.

The notion of “sustainable development” has had a short and tumultuous history, including a departure from economic reductionism by focusing on a multidimensional aspect and addressing the issues of its scope across many disciplines. It has become a project enabling a rethinking of capitalism based on the concept of a reformed type of capitalism. The purpose of this paper is to study this issue.

The paper is based on the following arguments: the presentation of sustainable development as a “vague” theory, an empirical proof of this vagueness with regard to corporate actions whose justification is based around the notion of sustainable development, and finally the ambiguities of the notion.

The notion of sustainable development raises the question of an apparent consensus on its correlates: solidarity, responsibility, equity, etc. It tends to establish a protean sense of the firms' responsibility, particularly the larger ones. The largely political dimension of the notion has today consequences on its usage. Sustainable development as addressed in the firm tends to take on the dimension of a management issue, which is likely to persist due to its larger political dimension.

The paper provides insight on the catch‐all dimension of the notion and its appealing rhetorical character and bases the ambiguity related with references to an “in‐between.” On the institutional level, it refers to a social and fair economy that stands arguably in between the state and the market. On the methodological level, it refers to heuristics of fear and hope.

Construction‐oriented discrete‐event simulation often faces the problem of defining uncertain information input, such as subjectivity in selecting probability distributions that result from insufficient or lack of site productivity data. This paper proposes incorporation of fuzzy set theory with discrete‐event simulation to handle the vagueness, imprecision and subjectivity in the estimation of activity duration, especially when insufficient or no sample data are available. Based upon an improved activity scanning simulation algorithm, a fuzzy distance ranking measure is adopted in fuzzy simulation time advancement and event selection for simulation experimentation. The uses of the fuzzy activity duration and the probability distribution‐modeled duration are compared through a series of simulation experiments. It is observed that the fuzzy simulation outputs are arrived at through only one cycle of fuzzy discrete‐event simulation, still they contain all the statistical information that are produced through multiple cycles of simulation experiments when the probability distribution approach is adopted.

The sample size formula is extensively used in work measurement. However, this formula, based on statistical techniques, demands that parameters should be precisely assessed. In some situations, when there is vagueness involved in the assessment of parameters, the results obtained using this formula could be erroneous. Redesigns this formula in a fuzzy environment where its parameters can be specified imprecisely. This gives “leeway” to the user in stating the parameters, in the sense that parameters can be specified in a range. The strength of fuzzy set theory lies in the possibility of quantifying and manipulating qualitative statements, vagueness, lack of data, or subjectivity of opinion.

For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania.

In recent years, a lot of research work has been done on trapezoidal interval type-2 fuzzy sets (TIT-2 FS), and many research works have been published. The trapezoidal interval type-2 fuzzy set helps effectively to represent the uncertainty comparatively than the type-1 fuzzy set. Taking advantage of this effectiveness, the authors extend the best multi-criteria decision making method (MCDM) for trapezoidal interval type-2 fuzzy sets. Here, ELimination and Choice Expressing REality III (ELECTRE III) method in the trapezoidal interval type-2 fuzzy set environment is proposed.

This analysis helps to the OECD countries to develop their level of innovation in the criteria. The authors are making this evaluation for the year 2018 based on the 31 criteria. Application of the proposed method expressed by evaluation of the national innovation capability problem. Based on the obtained results, the top five countries are United States, Switzerland, Canada, Germany and Japan.

The authors collected required data from different available data sources like OECD, IMD, USPTO, ITU and surveyed data reported by KISTEP. After collecting all the data from different sources, the authors calculated the standard values as KISTEP. After converting the standard values into trapezoidal interval type-2 fuzzy values, the authors construct a decision matrix based on these values. Then, the authors determined the possibility mean values and preference. Then, they calculated the concordance and discordance credibility degree values. Finally, they ranked OECD countries by the net credibility degree. The results are computed by using the MATLAB software.