A new fuzzy multi-criteria framework for measuring sustainability performance of a supply chain

Sustainable supply chain performance measurement is aimed at addressing environmental, social and economic aspects of sustainable supply chain management. It can be argued that it is not easy to reduce all dimensions of sustainable supply chain to a single unit. Then, the issue is that all valuations should somehow be reducible to a single one-dimensional standard. Multi-criteria evaluation introduces a framework to remedy this issue. As a consequence, multi-criteria evaluation seems to supply a proper and adequate assessment framework for sustainable supply chain assessment. In this study, a multi-criteria framework based on fuzzy entropy and fuzzy multi-attribute utility (FMAUT) is proposed in order to evaluate and compare the company performances in terms of sustainable supply chain. However, note that reducing all aspects of sustainable supply chain to a single unit using a multi-criteria framework may not be sufficient to satisfy all the needs of decision makers although it is used to evaluate sustainability performance of supply chains with respect to three aspects. Therefore, in this research, an alert management system is also developed to satisfy further requirements of users. The proposed frameworks are tested using data obtained from one of the middle sized Turkish grocery retailers.     

Thinking inside the box: A participatory, computer-assisted approach to scenario discovery

Scenarios provide a commonly used and intuitively appealing means to communicate and characterize uncertainty in many decision support applications, but can fall short of their potential especially when used in broad public debates among participants with diverse interests and values. This paper describes a new approach to participatory, computer-assisted scenario development that we call scenario discovery, which aims to address these challenges. The approach defines scenarios as a set of plausible future states of the world that represent vulnerabilities of proposed policies, that is, cases where a policy fails to meet its performance goals. Scenario discovery characterizes such sets by helping users to apply statistical or data-mining algorithms to databases of simulation-model-generated results in order to identify easy-to-interpret combinations of uncertain model input parameters that are highly predictive of these policy-relevant cases. The approach has already proved successful in several high impact policy studies. This paper systematically describes the scenario discovery concept and its implementation, presents statistical tests to evaluate the resulting scenarios, and demonstrates the approach on an example policy problem involving the efficacy of a proposed U.S. renewable energy standard. The paper also describes how scenario discovery appears to address several outstanding challenges faced when applying traditional scenario approaches in contentious public debates.     

A functional approach for studying technological progress: Application to information technology

This paper develops and assesses a broad functional category approach to arriving at metrics for assessing technological progress. The approach is applied to three functional categories of information technology — storage, transportation and transformation by first building a 100 plus year database for each of the three functional categories. The results indicate generally continuous progress for each functional category independent of the specific underlying technological artifacts dominating at different times. Thus, the empirical results reported in this study indicate that the functional category approach offers a more stable and reliable methodology for assessing longer time technological progress trends. Therefore, this approach offers the promise of being more useful in technological forecasting for large-scale change even as its ability to forecast specific dominant technological trajectories has been compromised.     

A functional approach for studying technological progress: Extension to energy technology

This paper extends a broad functional category approach for the study of technological capability progress recently developed and applied to information technology to a second key case—that of energy based technologies. The approach is applied to the same three functional operations—storage, transportation and transformation—that were used for information technology by first building a 100 plus year database for each of the three energy-based functional categories. In agreement with the results for information technology in the first paper, the energy technology results indicate that the functional approach offers a stable methodology for assessing longer time technological progress trends. Moreover, similar to what was found with information technology in the first study, the functional capability for energy technology shows continual—if not continuous—improvement that is best quantitatively described as exponential with respect to time. The absence of capability discontinuities—even with large technology displacement—and the lack of clear saturation effects are found with energy as it was with information. However, some key differences between energy and information technology are seen and these include:

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Lower rates of progress for energy technology over the entire period: 19-37% annually for Information Technology and 3-13% for Energy Technology.

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Substantial variability of progress rates is found within given functional categories for energy compared to relatively small variation within any one category for information technology. The strongest variation is found among capability progress among different energy types.

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More challenging data recovery and metric definition for energy as compared to information technology.

These findings are interpreted in terms of fundamental differences between energy and information including the losses and efficiency constraints on energy. We apply Whitney's insight that these fundamental differences lead to naturally modular information technology artifacts. The higher progress rates of information-based as opposed to energy-based technologies follows since decomposable systems can progress more rapidly due to the greater ease of independent as opposed to simultaneous development. In addition, the broad implications of our findings to studies of the relationships between technical and social change are briefly discussed.     

A predictive filtering approach for clarifying bibliometric datasets: an example on the research articles related to industry 4.0

ABSTRACT

This study proposes a filtering approach based on text classification and a fuzzy multi-criteria decision-making technique to select the relevant bibliometric data for further analyses in the scope of bibliometrics, scientometrics, and related methodologies. The proposed approach is illustrated on Industry 4.0 and internet of things which are the concepts that currently draw utmost attention with a growing number of research and applications. Accordingly, various findings are presented revealing the characteristics of the selected bibliometric data with the help of text and network analytics. The potential contribution of this study is two-fold such that the study not only suggests a novel approach for clarifying the retrieved bibliometric data but also emphasises the mainstream research areas and directions of Industry 4.0 along with the concept of the internet of things. Thus, an analysis framework with computing techniques has been used to reveal the characteristics of literature in a field of technology.     

A patent-based cross impact analysis for quantitative estimation of technological impact: The case of information and communication technology

The increasing syntheses and interactions between various technologies increase the usefulness of cross impact analysis (CIA) as a method for forecasting and analyzing them. Conventional CIA depends on an expert's qualitative judgment or intuition and thus it is difficult to evaluate quantitatively the impact of one technology on another. In this study, we employ patent analysis in CIA to examine such impacts between technologies based on multiple patent classifications. Patent information is used for facilitating quantitative and systematic approach in CIA. The distinctive feature and main contribution of the proposed approach is the overcoming of the limitations of conventional CIA, by employing conditional probabilities based on the patent information. The classification of patents, particularly the multiple classifications, is used to evaluate the relationships between technologies. As an illustration, a patent-based CIA with information and communication technologies (ICTs) was conducted. Firstly, the patent-based cross impact among ICTs was calculated. Secondly, the technology pairs were classified based on the cross impact score between ICTs. Thirdly, a cross impact network was constructed to identify the complex relation among ICTs. Finally, the changes in cross impact scores between technologies over time were analyzed. The results of this research are expected to help practitioners to forecast future trends and to develop better R&D strategies.     

The Delphi method, impeachment and terrorism: Accuracies of short-range forecasts for volatile world events

Two experiments examined the effects of iterated polling and feedback on prediction accuracy for volatile world events using the Delphi paradigm. In both experiments, participants predicted rapidly changing geopolitical events. The first experiment occurred during the litigation surrounding the Clinton/Lewinsky affair in 1998. Results indicated that feedback improved individual and group accuracy for predictions of whether an event would occur. These types of predictions derived from group consensus were approximately 90% accurate, which was significantly higher than the average individual participant's accuracy. Neither polling nor feedback had much effect on time course predictions. The second experiment occurred during the American military action against the Taliban regime in Afghanistan in 2001. In Experiment 2, participants were polled three times to determine if increasing the number of iterated polls would improve Delphi accuracy. The results showed that accuracy improved from the first to the second poll but not from the second to the third. The groups predicted whether these scenarios would occur with approximately 75% accuracy, which was significantly higher than the accuracy of any individual participant. Once again, the Delphi procedure did not enhance time course predictions in Experiment 2.     

RT Delphi: An efficient, “round-less” almost real time Delphi method

The authors have recently developed a new approach to performing a Delphi study that does not involve the use of sequential “rounds” and as a result, greatly improves the efficiency of the process and shortens the time to perform such studies. This paper describes this process, RT Delphi, and illustrates its use in a decision-making application drawn from the Millennium Project of the American Council for the United Nations University. The illustrative application involves setting priorities among strategies for dealing with anticipated terrorist activities that might be initiated by a single deranged individual.     

A new definition and framework for the development of a national technology strategy: The case of nanotechnology for Iran

In this research, we use the concepts of “national technology policy” as well as the “firm technology strategy” in defining a new definition for “national technology strategy”. Then, by examining several national technology strategies in a variety of fields in different countries the national nanotechnology strategy for Iran is developed. Furthermore, using capability-effectiveness matrix and SWOT analysis we identify strategies of nanotechnology development in Iran. Finally, considering other countries' strategies and the results of PROMETHEE Method, we prioritize different areas of nanotechnology for Iranian economy, and test for the validity of the extracted strategies.     

Partner country selection between development narratives and self-interests: A new method for analysing complex donor approaches

Partner country (PC) selection lies in the centre of development policy decision-making of donor countries and institutions, and plays a significant role in shaping aid patterns. This paper proposes a comprehensive analysis contrasting donor intentions in PC selection with actual aid flows. Having analysed selected members of the Development Assistance Committee of the Organization for Economic Cooperation and Development, namely, the European Union, France, Germany, Japan, Netherlands, Sweden, the United Kingdom and the United States of America, we suggest that (1) donors might not only be either altruistic or self-interested but also motivated by an intention to contribute to the provision of global public goods; (2) self-interest in aid provision can be an explicitly-stated strategy, contrary to what has been argued in the majority of the literature, which often treats self-interest as a non-stated donor intention; and (3) donors' self-interested intentions do not always lead to a less development-oriented donor approach.     

A new method for assessing the sustainability of land-use systems (II): Evaluating impact indicators

In the past decade, numerous indicators and indicator sets for sustainable agriculture and sustainable land management have been proposed. In addition to their interest in comparing different management systems on an indicator by indicator basis, land managers are often interested in comparing individual indicators against a threshold, or, in order to study trade-offs, against each other. To this end it is necessary to (1) transform the original indicators into a comparable format, and (2) score these transformed indicators against a sustainability function.This paper introduces an evaluation method for land-use-related impact indicators, which was designed to accomplish these tasks. It is the second of a series of two papers, and as such it links into a larger framework for sustainability assessment of land use systems.The evaluation scheme introduced here comprises (1) a standardisation procedure, which aims at making different indicators comparable. In this procedure indicators are first normalised, by referencing them to the total impact they contribute towards, and then they are corrected by a factor describing the severity of this total impact in terms of exceeding a threshold. The procedure borrows conceptually from Life Cycle Assessment (LCA) Impact Analysis methodology; (2) a valuation procedure, which judges the individual standardised indicators with regard to sustainability.This methodology is then tested on an indicator set for the environmental impact of a spinach production system in Northwest Germany. The method highlights mineral resource consumption, greenhouse gas emission, eutrophication and impacts on soil quality as the most important environmental effects of the studied system.We then explore the effect of introducing weighting factors, reflecting the differing societal perception of diverse environmental issues. Two different sets of weighting factors are used. The influence of weighting is, however, small compared to that of the standardisation procedure introduced earlier.Finally, we explore the propagation of uncertainty (defined as a variable's 95% confidence limits) throughout the standardisation procedure using a stochastic simulation approach. The uncertainty of the analysed standardised indicator was higher than that of the non-standardised indicators by a factor of 2.0 to 2.5.     

A hybrid visualisation model for technology roadmapping: bibliometrics,qualitative methodology and empirical study

Technology roadmapping offers a flexible instrument to portray development status in support of technology forecasting and assessment. This paper integrates bibliometrics with qualitative methodologies and visualisation techniques to construct a hybrid model for composing technology roadmaps. The mapping arrays details on the evolution of the technology under study and contributes to understanding the macro-technology development status. We generate a global technology roadmap for electric vehicles to demonstrate the approach in an empirical study.     

ESTEEM: Managing societal acceptance in new energy projects : A toolbox method for project managers

There is now a large literature dealing with the policy question of public participation in technical choice and technology assessment (TA). Files such as the mad cow crisis, genetically modified food, and the emerging nanotechnologies have been edified into a public problem, and have given place to a number of experiments and reviews about participatory arrangements. Much less attention has been devoted so far to the application of the TA framework to more local and limited projects-not yet and maybe never reaching the public problem status-and the management of their societal dimensions. Among them, new energy technology represents a very interesting field for investigation: many of the new energy enjoy a global positive public image whereas the local implementation of their implantation often raises societal questions and oppositions. This paper describes an original experiment conducted in the field of new energy technologies during which a participatory technology assessment inspired approach was applied to a number of individual and local projects. A framework methodology called ESTEEM was developed to facilitate such participatory process to take place, and it was tested and evaluated in 5 projects located in 5 different countries over Europe. A detailed discussion of the ESTEEM method and its application to one case study, a Carbon Sequestration project in The Netherlands, is provided. We show that a major question in the application in such participatory framework is to establish a reflective practice of project management based on situated and constructive interactions between project promoters and project stakeholders.     

A visual scanning of potential disruptive signals for technology roadmapping: investigating keyword cluster,intensity, and relationship in futuristic data

Technology roadmapping of today’s era is necessarily based on comprehensive scanning of various signals with the disruptive potential in future paths of market, product, and technology. Previous attempts of data-driven technology roadmaps have mainly focused on data from such sources as patents and literatures. However, as these sources catalogue posteriori trends of evolution, roadmaps based on these data cannot be counted on to predict disruptions. In this regard, futuristic data in technology foresight websites may provide a better source. The objective of this research, in response, is to develop a support system for technology roadmapping that uses futuristic data. To this end, we suggest keyword-based visual scanning approach involving three keyword maps, used in succession: keyword cluster map, keyword intensity map, and keyword relationship map. Particularly, keyword intensity map is designed using weak signal theory which can help identify the visibility, diffusion, and interpretation of signals.