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A new safety index known as Occupational Safety Evaluation Index (OSEI) is developed to evaluate and map the level of workplace safety in medium size iron and steel manufacturing industries (MSMIs) of Punjab. Delphi method is used to devise the OSEI based on a set of 40 key factors validated by content validity index (CVI). In order to determine the various obstacles in workplace safety, stepwise regression analysis is carried out using the statistical package for the social sciences (SPSS, version 20.0). The analysis reveals that factors such as organizational attributes, workplace layout and housekeeping, occupational exposures, personal protective equipment (PPE) and hygiene factors are the main obstacles for workplace safety in MSMIs. It is therefore recommended that the MSMIs should uplift these safety parameters to minimize the obstacles for better and safe working environment at the workplace. Hence, OSEI proves to be a useful tool to evaluate the safety performance of industries and by following the corrective measures suggested in this study, the level of safety in MSMIs of Punjab can be improved upon.

The cracking damage of the high-speed railway slab track seriously affects its durability and service life. The cracking condition index (CCI) for the China railway track system (CRTS) III prefabricated slab track and the corresponding calculation methods were proposed to realize the scientific management and guide the maintenance more reasonably. In order to ensure the objectivity and rationality of each parameter’s weight, first, the finite-element (FE) model of CRTS III prefabricated slab track with surface cracks was established to analyze the crack growth behavior, based on the fracture mechanics theory. The results show that the crack growth rate of transverse cracks at the same depth is greater than that of longitudinal cracks and significantly greater than that of through cracks. Then 437 valid questionnaires were obtained through expert consultation. Combining the subjective factors of expert evaluation with the objective factors of numerical simulation, the Delphi method and interval analytic hierarchy process (AHP) were used to establish the structural hierarchy, which could determine the weight of each parameter. After that, it was applied to an engineering example. The results show that the weights obtained by the comprehensive method combining the Delphi method and the interval AHP are more objective. Furthermore, the evaluation method was applied to the engineering example, obtaining the slab track CCI within [70.91, 72.83] points, which verified the rationality of the evaluation method. In short, the index evaluation method can quantitatively analyze the cracking severity of the track slab, which has important reference and practical value for line maintenance.

With the advent of the digital era, the demand for engineering and technological talents in the market is increasing. It is crucial to design a sustainable training and evaluation system suitable for engineering and technological innovation talents. However, traditional data evaluation models have problems with unsuitable evaluation indicators and low model accuracy. Therefore, the paper selects the decision-making-oriented evaluation model to build the basic talent training evaluation indicators, and design expert questionnaires based on the Delphi method to screen indicators. Moreover, the paper also combines the adaptive genetic algorithm optimised backpropagation neural network to establish a talent cultivation evaluation model, and conducts simulation experiments using MATLAB to verify its feasibility. The results showed that the evaluation accuracy $R$ value of the research model was 0.99635, and the fitness value was 1.34, which was 0.5 higher than the unmodified model and achieved good evaluation results. At the same time, by comparing with the traditional genetic algorithm optimised model and the unimproved backpropagation model, the average evaluation accuracy of the research model increased by 66.44% and 13.59%, and the recall rate increased by 10.79% and 23.96%. The research model has improved the accuracy of evaluation, and its adaptability has also been enhanced, achieving superior evaluation results, which has important value in the cultivation of engineering and technological innovation talents.

Aiming at the low success rate of incubation investment of China’s technology-based start-ups, how to scientifically evaluate technology-based start-ups has become an important issue that needs to be faced. Considering the expert consultation characteristics of the Delphi method is extremely suitable for decision-making problems in the field of uncertainty, as well as the strong nonlinear mapping ability and learning ability of the backpropagation neural network (BPNN). According to the characteristics of the evaluation object and following the principle of index selection, the study uses the Delphi method to determine the evaluation index system suitable for technology-based entrepreneurial enterprises in the current environment and obtain the scores of each index. Based on the established evaluation index system, the BPNN evaluation model is further constructed, and its parameters are optimised to improve its performance. Aiming at the problem that it is easy to fall into a local optimal, a genetic algorithm (GA) is used to optimise it, and a GA-BPNN model is constructed. The comprehensive capability of GA-BPNN is evaluated by using the excellent nonlinear characteristic analysis ability of GA-BPNN to provide a reference for important decisions such as investment. Using BPNN simulation, it was concluded that the correct rate of evaluation of qualified enterprises was between 23.32% and 89.99%, with an average correct rate of 58.32%. The average correct rate was 80.99%. The evaluation accuracy rate was unstable and the average accuracy rate was low. The optimised GA-BPNN model had an average evaluation accuracy rate of 80.32% for qualified enterprises and 93.66% for unqualified enterprises, and the average evaluation accuracy rate increased by 21.99% and 12.66%, respectively. The effectiveness of the model and algorithm was verified. It shows that the GA-BPNN model can be used as an effective tool for the evaluation and screening of technology-based entrepreneurial enterprises. The evaluation system of technology-based entrepreneurial enterprises established by research is scientific and can be applied in practice.

The main goal of this paper is to show how the Delphi method works as a management tool when analyzing technology evolution. The paper also provides insights on how thin computing and open source can affect the future IT infrastructure development. The primary data was collected in a three round Delphi study consisting of the following interest groups: (1) Developers of open source thin computing, (2) Industrial experts, (3) Representatives of academic institutes. The Delphi method represents a workable research tool in technology management field to capture multifaceted and enriched view about industry evolution.

The growing global demand for efficient and sustainable urban mobility in metropolitan areas has created innovative approaches to new modes of transportation and vehicles. Using the Delphi method, this study explored the prospective development of urban air mobility (UAM), specifically the emergence of air taxis or vertical take-off and landing (VTOLs). The two-staged study examined 25 projections regarding technological and infrastructural aspects to propose a future scenario for UAM and air taxis for the next 5–10 years. The questioned experts confirmed most of the proposed statements from both areas but were undetermined regarding certain technological aspects. Considering the crucial impacts of regulation and certification as well as consumer perception and acceptance for UAM and air taxis, further research on these topics and their correlation is suggested.

Among generic technology management activities, rapid technology identification and selection stand as the significant determinants of technology adoption success in the digital transformation era. Especially for manufacturing SMEs in developing countries, rapid digital technologies are critical since they struggle to protect their competitiveness in global value chains threatened by digitalization. Previous studies introduce various multi-criteria decision-making model-based approaches to identify and select appropriate manufacturing technologies. However, these approaches were relatively rigid and required an advanced understanding of the technology for criteria and alternative settings and evaluation. Decision-makers need more flexible and scalable contextual frameworks for technology selection in digitalization. Since digital technologies offer both benefits and challenges, the decision-making models should reflect this dialectic nature of Industry 4.0 adoption and contextually optimize their decisions by combining multiple quantitative methods for technology identification and selection. Besides, case studies on digital technology selection are rare in manufacturing SMEs from developing country context in the literature. In this context, this study proposes a technology selection framework that utilizes the three dimensions (industry 4.0 technologies, benefits, and challenges) and combines AHP with a QFD-inspired intervention matrix and an optimization model by Mixed Integer Programming (MIP). The proposed model is validated with a case study from the automotive supplier industry in Turkey with the data provided from interviews and a Delphi survey with 11 experts from the digitalization value chain of the selected industry. Case study results revealed that the highest benefits of industry 4.0 lie in process/quality efficiency improvement and reduced inventory. At the same time, data analytics and sensor technologies occurred as the most critical tools. Significant challenges of digital technology adoption are insufficient expert know-how and budget constraints.

Forecasting the future is an important aspect of strategic planning. In recent years, an increasing number of corporate planners and forecasters have been turning to forecasting techniques to assist them in management decision-making. This paper presents a fuzzy management decision support system for scenario analysis. The system, developed in dBFAST, comprises two modules: data input and scenario generation. It is aimed at emulating the expert’s reasoning process in forecasting. It adopts a hybrid technique—a combination of fuzzy Delphi analysis and fuzzy reasoning—for problem solving. Three widely accepted forecasting techniques—the Delphi method, trend impact analysis and cross-impact analysis—are briefly reviewed. The hybrid technique developed and the details of the fuzzy management decision support system for scenario analysis are described. Using a case study on the penetration of computer-integrated manufacturing (CIM) in the electronics industry in Singapore as an example, the performance of the system is discussed.

Environmental problems have spatial origins and consequences. Hence, effective stakeholder participation demands the integration of comprehensive facilities for understanding the spatial components that affect environmental change. This study develops the Collaborative Spatial Delphi (CSD) methodology to embed spatial thinking, conceptualise the dynamic mechanisms, and assess the effectiveness of the resulting participatory process. The CSD uses a collaborative geographic information system (GIS) and the Delphi procedure in a descriptive decision-making framework that integrates diverse stakeholder knowledge for spatial awareness, understanding, and negotiated outcomes. The CSD synthesises relevant theories to conceptualise the participation mechanisms, and an application of the methodology to urban green spaces planning in Montreal, Canada is presented. The results suggest that a deficiency in technical background is not a barrier to effective use of spatial technology in participatory planning. The methodology enhanced many spatial facets of the participation process and was evaluated as effective in achieving negotiated outcomes.

According to the newest classification of the Spatial Planning Act of the Land Planning Act in Taiwan, land space is divided into environmental conservation zones, marine resource zones, agricultural development zones, and urban and rural development zones. Among the above zones, environmental conservation zones are the most important for environmental resource conservation. The purpose of this study is to construct evaluation levels for environmental conservation zones, and to construct an evaluation index system after determining the decision criteria and their interrelationships, thereby identifying the key factors based on the evaluation criteria and indexes in decision-making process. The research method combines the multi-criteria decision-making and fuzzy theory. The indexes of optimal scheme and appropriate resource utilization methods are selected. An easy-to-use and concise planning evaluation model is constructed, with the aim to provide references for local governments in formulating policies, so that the utilization of land space can be sustainable.

Over the years, renovation of old school buildings and campus environment have always been planned based on the philosophy of sustainable development, and expectation that the development of school campuses matching with the requirement of green architecture and green energy management can reach a sustainable, ecological and healthy goal. Focusing on sustainable development of elementary school campuses, this study discussed the correlation between campus sustainable planning and green building indices, through literature analysis. Initially, 9 indices and 28 criteria have been developed through expert interviews for the establishment of a sustainable campus environment diagnosis and renovation evaluation framework. The expert questionnaire based on Delphi method was then used to get expert consensus for the evaluation framework with 9 indices and 20 criteria. Afterward, the Analytic Hierarchy Process (AHP) questionnaires were used to determine relative or absolute weighted values of these criteria by building contrast matrices to facilitate the establishment of a scoring table for sustainable campus diagnosis and renovation assessment. Finally, the scoring table was applied to an existing elementary school campus to diagnose the sustainability problems it had encountered. It is found that the school has, among the 20 evaluation sub-criteria, 5 sub-criteria urgently to be retrofitted, 9 criteria to be improved and 6 criteria passed the assessment with a total score of 62.914.