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Presentation of the different industrial carbon linkages of India. The purpose of this paper is to understand the direct and indirect impact of these industrial linkages.

This study uses a hypothetical extraction method with its various extensions. Under this method, different carbon linkages of a block are removed from the economy, and the effects of carbon linkages are determined by the difference between the original and the post-removal values. Energy and non-energy carbon linkages are also estimated.

“Electricity, gas and water supply (EGW)” at 655.61 Mt and 648.74 Mt had the highest total and forward linkages. “manufacturing and recycling” at 231.48 Mt had the highest backward linkage. High carbon-intensive blocks of “EGW” plus “mining and quarrying” were net emitters, while others were net absorbers. “Fuel and chemicals” at 0.08 Mt had almost neutral status. Hard coal was the main source of direct and indirect emissions.

Net emitting and key net forward blocks should reduce direct emission intensities. India should use its huge geographical potential for industrial accessibility to cheaper alternative energy. This alongside with technology/process improvements catalyzed by policy tools can help in mitigation efforts. Next, key net-backward blocks such as construction through intermediate purchases significantly stimulate emissions from other blocks. Tailored mitigation policies are needed in this regard.

By developing an understanding of India’s industrial carbon links, this study can guide policymakers. In addition, the paper lays out the framework for estimating energy and non-energy-based industrial carbon links.

This paper aims to identify key sectors in carbon footprint responsibility, an introduced concept depicting CO₂ responsibilities allocated through the supply chain containing sectoral activities and interactions. In detail, various key sectors could be identified according to comparative advantages in trade, sectoral linkage and sectoral synergy within the supply chain.

A semi-closed input–output model is used to make the household income–expenditure relationship endogenous through the supply chain where sectoral CO₂ emissions are calculated, and the production-based responsibility (PR) principle is evaluated. Thus, according to “carbon footprint responsibility”, modified hypothetical extraction method is applied to decompose sectoral CO₂ in terms of comparative advantages in trade, sectoral linkage and synergy. Finally, key sectors are identified via sectoral shares and associated decompositions in carbon footprint responsibility.

Compared to 2005, in 2012, the PR principle failed to track sectoral CO₂ flow, and embodied CO₂ in import and interprovincial export increased, with manufacturing contributing the most; manufacturing should take more carbon responsibilities in the internal linkage, and tertiary sectors in the net forward and backward linkage, with sectors enjoying low carbonization in the mixed linkage; inward net CO₂ flows of manufacturing and service sectors were more complicated than their outward ones in terms of involved sectors and economic drivers; and residential effects on CO₂ emissions of traditional sectors increased, urban effects remained larger than rural ones and manufacturing and tertiary sectors received the largest residential effects.

The value of this paper is as follows: the household income–expenditure relationship got endogenous in intermediate supply and demand, corresponding to the rapid urbanization in megacities; key sectors were observed to change flexibly according to real sectoral activities and interaction; and the evaluation of the PR principle was completed ahead of using a certain CO₂ accounting principle at the city level.

Traceability is an increasingly important tool for reducing food safety risks and managing supply logistics. Given the costs of implementing and maintaining traceability systems, it is crucial to understand consumer willingness to pay (WTP) for traceable products.

The authors conducted a scoping review to collate the existing literature on consumer WTP for traceability in food products to determine the nature of the evidence base and to identify research gaps.

A total of 77 articles were included in the review. The number of studies published per year generally increased over the review period, and China and the United States were the most common countries in which studies were conducted (43.6 and 14.1% of total studies, respectively). All but one of the studies investigated at least one factor that might influence consumer WTP for traceability, the most common of which was socio-demographic characteristics (72.7%). Three-quarters of studies used hypothetical methods to elicit WTP values (75.3%), whereas one-quarter used non-hypothetical methods (24.7%). Most studies included some measure of preference heterogeneity (83.1%).

There is some potential for systematic bias in the evidence due to the predominance of studies from only a few countries and the possible presence of hypothetical bias. These potential biases could be corrected through future research.

To the authors’ knowledge, no previous study systematically and comprehensively identifies and summarizes the evidence base on consumer WTP for traceable food products.

Given the critical role of project prioritization and selection process in Six Sigma efforts, this study aims to analyse the relevant literature to answer this question: What types of project prioritization and selection methods have been used in Six Sigma research?

The study implemented the systematic literature review (SLR) method to identify and review all relevant previous studies.

The study revealed that 59 articles focused on the topic used 111 methods, analytic hierarchy process appeared as the most frequently used method with 12 articles (20%) and one-third of the methods used in the current Six Sigma project selection literature contained multi-criteria decision-making methods. In total, 61% of 59 articles were not published in the journals ranked by the ABDC’s list. Only 17% of the articles reviewed in this study were published in journals ranked as B category and 12% of the articles were published in A category journals.

The findings of this literature review may help Six Sigma practitioners and researchers accurately identify project prioritization and selection methods, considering that qualitative and quantitative scientific methods guarantee to make better decisions than “gut feelings” of the decision makers in this process.

Although a variety of studies focused on the topic, an SLR is lacking in the area of Six Sigma project prioritization and selection. Therefore, this study was constructed using the SLR method to analyse the topic.

The purpose of this paper is twofold: primary, to argue that the profits method, specifically a discounted cash flow (DCF)-based profits method, should be the preferred method of valuation when valuing specialised property. Secondary, to make technical recommendations in the application of the method.

Literature was reviewed on the theory of the profits method as well as physical valuations performed in practice. Improvements for the profits method are suggested from the review of six valuations conducted in South Africa in the specialised property sectors. A qualitative approach is followed in the research as broad principles are extracted from the valuation reports as implications and improvements for the profits method.

The profits method is more flexible and sophisticated than the cost approach in taking into account systematic and unsystematic risk. The profits method is more accurate than the cost approach in delivering a true reflection of the value of specialised property for any purpose but specifically for mortgage lending purposes and reduces the credit exposure risk of financial institutions. It also decreases pricing inefficiencies to be exploited by buyers and sellers.

Three improvements to the profits method are suggested. First, revenue could be forecasted based on a probability-weighted approach. Second, a modified capitalisation rate is suggested to the capitalisation rate formula in the calculation of G. Third, a market rental aggregation anchoring and judgement-based approach is suggested as rationale for determining the hypothetical rental split.

There seems to be a general lack in literature on the profits method of valuation and its application to specialised properties, specifically a DCF-based approach, with this paper being a technical contribution to the body of knowledge on this topic.

Summarization of an entire web site with diverse content may lead to a summary heavily biased towards the site's dominant topics. The purpose of this paper is to present a novel topic‐based framework to address this problem.

A two‐stage framework is proposed. The first stage identifies the main topics covered in a web site via clustering and the second stage summarizes each topic separately. The proposed system is evaluated by a user study and compared with the single‐topic summarization approach.

The user study demonstrates that the clustering‐summarization approach statistically significantly outperforms the plain summarization approach in the multi‐topic web site summarization task. Text‐based clustering based on selecting features with high variance over web pages is reliable; outgoing links are useful if a rich set of cross links is available.

More sophisticated clustering methods than those used in this study are worth investigating. The proposed method should be tested on web content that is less structured than organizational web sites, for example blogs.

The proposed summarization framework can be applied to the effective organization of search engine results and faceted or topical browsing of large web sites.

Several key components are integrated for web site summarization for the first time, including feature selection and link analysis, key phrase and key sentence extraction. Insight into the contributions of links and content to topic‐based summarization was gained. A classification approach is used to minimize the number of parameters.

The purpose of this paper is to employ a mixed methods design to assess the applicability, reliability and validity of Miller's scale of environmental uncertainty.

Using 759 questionnaires and eight personal interviews from three countries throughout four phases of scale assessment, the authors re‐operationalized Miller's scale to be more applicable to Arab countries. Phase 1 refines the scale with reference to the new context in which the authors applied it. Phase 2 eliminates poor performing items, using exploratory factor analysis. Phase 3 examines the generalizability of the modified scale in the Arab world. Finally, Phase 4 assesses the criterion‐related validity of the scale.

The authors' assessment of Miller's scale suggests that several changes in the scale are necessary to be more applicable in Arab countries. The results of the combined sample are consistent with the hypothetical structure of constructs and have four factors: product, competition, government and policies, and economy.

This study paid attention to the conceptualization and operationalization of strategic management research variables. Moreover, examining the Miller's scale in the Arab region could enhance the generalizability of this scale. Finally, the authors' longitudinal research, with its four samples, is another contribution.

The purpose of this paper is to develop a new method to extract medical temporal information from online health communities.

The authors trained a conditional random-filed model for the extraction of temporal expressions. The temporal relation identification is considered as a classification task and several support vector machine classifiers are built in the proposed method. For the model training, the authors extracted some high-level semantic features including co-reference relationship of medical concepts and the semantic similarity among words.

For the extraction of TIMEX, the authors find that well-formatted expressions are easy to recognize, and the main challenge is the relative TIMEX such as “three days after onset”. It also shows the same difficulty for normalization of absolute date or well-formatted duration, whereas frequency is easier to be normalized. For the identification of DocTimeRel, the result is fairly well, and the relation is difficult to identify when it involves a relative TIMEX or a hypothetical concept.

The authors proposed a new method to extract temporal information from the online clinical data and evaluated the usefulness of different level of syntactic features in this task.

The purpose of this paper is to perform a comparative assessment on working of the existed subassembly identification (SI) methods, which are widely practiced during the product development stage and to propose an improved method for solving the SI problem in assembly sequence planning (ASP).

The cut-set method is found as a suitable method among various knowledge-based methods such as the theory of loops, theory of connectors and theory of clusters for the workability enhancement to meet the current requirements. Necessary product information is represented in the matrix format by replacing the traditional AND/OR graphs and the advanced predicates are included in the evaluation criteria.

The prominent methods in SI are followed a few of the predicates to avoid complexity in solution generation. The predicate consideration is found as the most influencing factor in eliminating the infeasible part combinations at SI. However, the quality of identified subassemblies without advanced predicates is not influencing the solution generation phase but practical applicability is affecting adversely.

The capability of performing SI by the cut-set method is improved to deal with the complex assembly configurations. The improved method is tested by applying on different assembly configurations and the effectiveness is compared with other existent methods of ASP along with the conventional method.

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).

To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.

To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.