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To outsource part of their work, organizations are looking for suppliers who also have green criteria with other criteria. Selecting suppliers begins with the definition of potential suppliers and then selects the best among them. This study aims to present a two-part approach for selecting suppliers consisting of suppliers’ prioritization.

In the first part, the criteria that influence on selecting the suppliers have been identified and extracted using the literature review and experts’ opinion which consists of 19 criteria. Then, these criteria were evaluated by the content validity ratio index and using experts’ opinions, and finally, 16 criteria were selected for selecting green suppliers in a polyethylene’s products producer company in Iran. In the next step, suppliers are selected in a green supply chain using multi-criteria decision-making methods such as Dempster–Shafer theory and grey relationship analysis, which is a strategic decision.

This study attempts to improve the level of reliance on the whole uncertain degree by combining Dempster–Shafer theory and grey relational analysis (GRA), which makes the grey analysis method more robust and its results more reliable. The findings show that Supplier 4 is ranked as first within six suppliers.

Using GRA and Dempster–Shafer theory for green supplier selection problem in polyethylene industry is the novelty of this work.

This paper proposes a multi-layer hybrid decision-making approach to evaluate the capability alternatives for developing a collaborative network to operate in the international market.

The present study is contextualised in the Iranian pistachio export industry. An extensive review of the state-of-the-art literature on supplier collaboration was conducted to identify key capabilities that are essential to establish a collaborative network. The set of defined capabilities were then optimised through interviews with 14 experts from the relevant industry, academics and export authorities. A combination of the fuzzy Delphi method and the best–worst method (BWM) approach was, respectively, used to reduce the number of capability alternatives and assign priority weights to these alternatives. Subsequently, a weighted aggregated sum product assessment method (WASPAS) was employed to rank and evaluate the ability to creating a collaborative network for the export of pistachio.

From the extant literature review, 18 capabilities for the formation of coordination networks in the international markets were identified. Then, the prominent indicators in forming a global network were extracted. After ranking the top pistachio export countries/regions to formalise an efficient collaborative network, it was revealed that although Iran exports approximately 30% of the global market, it falls behind the USA and European Union. The competitors have scored higher in critical criteria, including “trust and commitment”, “strategy and management”, “managerial control and standardization” and “financial resources”.

The proposed hybrid approach encompassing fuzzy Delphi–BWM–WASPAS offers to solve the capability evaluation and selection as well as ranking the possible alternative to formalise a collaborative network in an integrated fashion. This combination of methods is capable to first identify the most important factors, then measuring their importance and eventually rank the possible alternatives. The suggested framework provides an approach to deal with the uncertainty of global collaborative network formation.

The construction organisations in developing countries are lagging in digital technology usage; hence, they are still characterised by poor project delivery and technological backwardness. To checkmate this problem, partnering with other organisations was proposed, while critical factors needed for successful digital partnering of construction organisations were assessed.

The study adopted a qualitative research approach. Delphi method was used to get experts' opinion on some identified factors necessary for successful digital partnering. The experts for the study were selected using defined criteria, and a combination of interquartile deviation, Kendall's coefficient of concordance and chi-square was used to achieve robust consensus among respondents. Mann–Whitney U test was also used to ascertain the difference in perception of experts.

The findings revealed trust in digital partners, top management support and digital partner selection as the three key success factors for partnering. Other factors that can be considered alongside these main factors are the creation of a common goal, a long-term commitment, effective communication, proper conflict resolution and structured as well as continuous digital training, workshops and meetings.

Instead of going through the digitalisation journey alone, construction organisations, particularly in a developing country like South Africa, stand a better chance of surviving the dynamic construction and digital environment by partnering with other organisations within and outside the industry. Carefully selecting the right partner, trusting in their capability and ensuring constant commitment is necessary for the success of the process.

The value of this study lies in its ability to showcase the critical success factors needed for effective digital partnering, an aspect that lacks adequate consideration in the digitalisation of construction industry discourse.

The selection of experts for Delphi studies is crucial for the quality of the forecast results and the information taken into account. In the past, this has usually been done by selecting participants according to their reputation, although this approach is questionable in terms of reaching the most knowledgeable participants having new, relevant and valid information. In this context, this paper aims to propose to operate a prediction market alongside Delphi studies and select participants based on their trading behaviour in the market for the Delphi study.

Based on more than three years of historical prediction market trading data, the authors verify attributes that indicate insightful trades, as previously discussed in the finance literature, by using regression and classification trees.

The paper contributes attributes of trading behaviour that are theoretically derived from literature and potentially related to informed traders. These are tested and evaluated on historical prediction market data. Especially, the trading volume, the spread at the moment of trading and the market maker attribute seem to predict informed traders the best.

Algorithms based on identified attributes can be used to objectify the selection of experts for Delphi studies with potential gains in terms of the amount of information considered.

This study is aimed to identify the attributes for a valuation approach of flood risk exposure, in particular for residential property. With frequent flood events in Malaysia, there is a need for valuation methods to evolve and represent the increased risk of natural disasters.

This study employed the Delphi method which is a systematic and interactive research technique in obtaining variables for a valuation approach for residential property exposed to flood risk.

Results from the Delphi method revealed four categories of attributes, namely environmental, locational, structural and economical.

The findings from this research will transform the valuation approach in Malaysia to identify the value of residential property exposed to flood risk. The determination of variables will represent the current risk in valuations, especially for residential property in flood-prone areas.

The purpose of this paper is to evaluate expert systems (ES) for selection of material handling (MH) equipment on their use of information and generation of equipment, and provide guidelines that can enhance developing them in the future.

Data envelopment analysis (DEA) is used to evaluate efficiency of ES on their use of information and generation of equipment. Characteristics of benchmark ES are identified to serve as guidelines in developing future ES.

Results of DEA indicate that most ES use a large amount of information that does not commensurate with the number and variety of equipment they generate.

The ideal MH equipment for a situation is not known whether it is selected by ES or other procedures. Therefore, this study focusses on efficiency of ES in using information to generate MH equipment without regard to whether ES produce the right equipment for a situation or not.

Developers of future ES should consider the efficiency of an ES in using information and generation of equipment, in addition to considering its functions and methodologies. They should utilize means similar to those employed by benchmark methodologies and other ones that can be thought of to economize information and generate more number and variety of equipment, and thus render ES more useful to facility designers and manufacturing managers.

The paper presents the first evaluation of ES for selection of MH equipment. The evaluation performed should enhance development of future ES in this field, and can be extended to ES in other application domains.

This study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment.

A multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM).

The criterion of “defining clear and real objectives” was ranked first, “project investment return period” was ranked second, “minimum changes in the predicted range” was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal.

This study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and screens the evaluation indicators. Furthermore, the weights of the evaluation indicators are determined using the fuzzy BWM based on the consistency of opinions.

The purpose of this paper is to understand the solicitation of outside experts in the upstream phase of innovation projects, which fall within the scope of the exploration and which take place within a context of radical uncertainty: how are these experts identified, selected and mobilised? While companies are compelled to manage exploration projects, the processes underlying the expansion of knowledge in these projects are not well known.

Based on the literature, this paper first presents a conceptual view of the notion of expert. Then, the research question is analyzed by means of a case study of a polar expedition. The project leader seeks a knowledgeable person who has never been identified as an expert, but whose knowledge is essential.

The expert appears both in his cognitive and social dimensions. Moreover, he emerges out of the situation, on the basis of neither strong nor weak signals. The rationality of expert solicitation falls within a pragmatic logic where the acquired knowledge must reduce the uncertainty so that the project can progress. The learning process enables to increase gradually the knowledge of the actor but also to build the legitimacy required in order to have access to the expert.

Findings can be translated in more general situations. Indeed, polar expeditions projects and exploratory innovation projects (Garel and Lièvre, 2010) possess some common characteristics: lack of knowledge concerning, timing issues, need to implement a pragmatic, enquiry-based learning. These projects strongly rely on external expert knowledge. This case study suggests that, while it may be useful, planning should not strictly define the course of action. A central competence of the project leader is to manage the duality between planning and adaptation. This implies the ability to adapt, to detect and to assess human resources and knowledge flows rapidly, as well as to weave social links inside and outside the organisation.

The existing literature offers a comprehensive view of experts in an organisation. However, the questions of expert selection and identification remain open. This paper fills a gap in the literature concerning the way experts are identified and selected. The case study shows that identifying experts does not solely depend on weak signals (reputation) or on strong signals (the expert’s social status). Rather, the expert emerges in the situation, in an unexpected way. The expert’s social dimension is not sufficient and one must look to the cognitive roots of the expertise. On the other hand, the fact is emphasised that the expert is a social construct which emerges from the solicitation process.

Cyberstalking is a growing threat to society, and policymakers should address it utilizing the input of constituents. For this, two key components are required: actionable objectives informed by the values of society and the means of implementation to maximize their potential benefits. The process should be guided by the constituent's values, requiring the elicitation of intrinsic values as individual preferences that are extrapolated to society at large.

The authors utilize Keeney's (1990) public value forum and Sen's (1999) social choice theory (Sen, 1999) to elicit and convert these intrinsic values to serve as the basis for developing public policy to prevent cyberstalking.

The results demonstrate a strong desire by participants to have clear regulations, policies and procedures developed in concert with industry and enforced by the government that elucidate required protections against cyberstalking in combination with strong technical controls. These policies should guide technical control development and implementation, but leave ultimate control in the hands of technology users to decide what controls they want to utilize.

This study is the first to utilize Keeney's (1988) public value forum in the context of cyberstalking to develop quantitative measures regarding technology users' desired cybersecurity protections against cyberstalking. The authors provide a decision-making framework for policymakers to develop a new policy based on the input of their constituents in a manner that maximizes their potential utility and ultimate benefit.