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This study aims to examine how entrepreneurship education influences intentions for starting a technology venture among science, technology, engineering and mathematics (STEM) students with particular attention to gender differences. This study builds on the model of entrepreneurial event and social role theory to assess the impact of entrepreneurship education on feasibility, desirability and intentions for technology entrepreneurship.

The hypotheses are tested with a sample of 879 Bulgarian science and engineering students from 15 universities. To test the models, this study uses ordinary least squares and logistic regressions with robust standard errors and Hayes mediation analysis with bootstrap bias-corrected confidence interval estimations for indirect effects. Two-stage Heckman regressions to control for sample selection bias and other robustness checks including propensity score matching were used.

Results show that entrepreneurship education, measured as participation in an entrepreneurship course, has a stronger impact on feasibility, desirability and intentions for technology entrepreneurship for female STEM students compared to their male counterparts. As such, this study supports the notion that entrepreneurship education could be part of a solution to counteract societal norms that position technology entrepreneurship as a less desirable and/or less feasible choice for women in STEM. However, attention should be paid to the operationalization of entrepreneurship education, as other measures of entrepreneurship education (role models, entrepreneurship education support) did not have a moderation effect with gender.

The authors assume a positive correlation between entrepreneurial intentions and entrepreneurial behavior. Future studies should include actual entrepreneurial behavior to paint a more complete picture of the effect of entrepreneurship education.

Little is known about the role of entrepreneurship education in the field of technology entrepreneurship, and even less about the potential gender differences in entrepreneurship education among STEM students. The study contributes to the literature by examining factors that could help close the persistent gender gap in technology entrepreneurship.

The present study is descriptive research in terms of purpose, descriptive analysis in terms of nature and cross-sectional research in terms of time. The study’s statistical population includes all employees and managers of the China City Organization selected as sample members using random sampling method and Krejcie table of 242 people. The questionnaire was modified and revised based on the goals, tasks and mission of the target organization to collect information. In data analysis, due to the normality of data distribution, the structural equation modeling method is used to evaluate the causal model, reliability and validity of the measurement model. Evaluation and validation of the model are done through the structural equation model. Questionnaire-based model and data are analyzed using Smart PLS 3.0. The main purpose of this study is to assess the feasibility of implementing the human resource payroll management system based on cloud computing technology.

New technologies require innovative approaches for creating valuable opportunities in an organization to integrate the physical flows of goods and services and financial information. Today, cloud computing is an emerging mechanism for high-level computing as a storage system. It is used to connect to network hosts, infrastructure and applications and provide reliable services. Due to advances in this field, cloud computing is used to perform operations related to human resources. The role, importance and application of cloud computing in human resource management, such as reducing the cost of hardware and information software in hiring, job planning, employee selection, employee socialization, payroll, employee performance appraisal, rewards, etc., is raised. This way, human resource management teams can easily view resumes, sort candidates and observe and analyze their performance. Cloud computing is effective in implementing human resource payroll management systems. Therefore, the primary purpose of this study is to assess the feasibility of implementing the human resource payroll management system based on cloud computing technology.

Testing the research hypotheses shows that the dimension desirability of ability and acceptance is provided in dimensions related to the minimum conditions required to implement cloud computing technology in the organization. For this reason, the feasibility of implementing the systems based on cloud computing in companies must be considered.

This study also has some limitations that need to be considered in evaluating the results. The study is limited to one region. It cannot be assured that the factors examined in other areas are effective. The research design for this study is a cross-sectional study. It represents the static relationship between the variables. Since cross-sectional data from variable relationships are taken at a single point in time, they are collected in other periods. As a proposal, future researchers intend to investigate the impact of Enterprise Resource Planning (ERP) systems based on cloud computing.

The research also includes companies, departments and individuals associated with systems based on cloud computing.

In this paper, the feasibility of implementing the human resource payroll management system based on cloud computing is pointed out, and the approach to resolve the problem is applied to a practical example. The presented model in this article provides a complete framework to investigate the feasibility of implementing the human resource payroll management system based on cloud computing.

The purpose of this paper is to present a decisions support tool that can be applied in initial stages of design, for evaluating the investment feasibility of changeable and reconfigurable manufacturing design concepts, based on future demand predictions and their uncertainties. A quantitative model is proposed, which evaluates the discounted value of capital and operating costs of changeable manufacturing design concepts, based on essential characteristics regarding their type and extent of changeability.

Quantitative empirical modeling is applied, where model conceptualization, validation, and implementation are central elements, using two Danish manufacturing companies as cases.

The applicability of the model is demonstrated in the two case companies, highlighting differences in type, extent, and level of feasible changeability, as a result of differences in product and production characteristics.

Further studies of changeability implementation should be conducted across industrial fields in order to generalize findings.

There is currently limited support for the conceptual design phase of changeable and reconfigurable manufacturing, where critical decisions regarding type, extent, and level of changeability must be made, regardless of high degrees of uncertainty about future demand scenarios.

This paper expands previous research on design for changeability and reconfigurability, by explicitly considering changeability as a capability that can be enabled in various ways for various purposes in different industrial contexts. The proposed model and the case implementations provide important knowledge on the transition toward changeability in industry.

This paper seeks to set out opportunities for the development of a UK‐focused feasibility and sizing model utilising linear programming.

Optimisation of the model is conducted using integer linear programming developed using Excel Solver.

When compared with comparable alternatives, the model is shown to be particularly useful as its functionality is embedded in resource intensive prime mover specifications obtained from seven real industrial cases.

The study acknowledges the limitation of utilising sizing data primarily obtained from secondary sources to develop the model.

The practical usefulness of this model is that it has been built using “real”, as opposed to simulated‐data. When compared with comparable alternatives, the model is shown to be articularly useful as its functionality is embedded in resource intensive prime mover specifications obtained from seven real industrial cases.

The purpose of this study is to solve five key brownfield valuation problems.

This aim is achieved by using doctoral research on integrating the scientific process into the appraisal process. The first objective is demonstrating why four of the problems require solutions prior to solving the first problem, a valuation procedure for formerly used sites. A second objective is to use empirical data from appraisals to reveal why existing methodology is not reliable – because it does not solve the four problems.

The resulting findings are that a developmental model that incorporates the Triad approach to quantifying environmental uncertainty, initially used in the USA, simulates a process used by buyers to establish the price paid for brownfields with contaminated land.

The practical implication that results from this research is that valuers need to emulate the buyer's process when valuing this property type. Prescriptive procedures for valuation requiring the use of scientific methods, as used in the Triad process, need to be set forth to quantify the atypical uncertainties in valuing this property type. The results of this research should be of significant interest to all stakeholders that are involved in brownfield redevelopment, so that they can insure that their needs will be met by improved feasibility analysis.

This research is unique in that it is the first empirical test of the reliability of the valuation of brownfields that need to undergo a time‐consuming and often expensive soil remediation process.

This paper develops a framework to study the potential feasibility to telework knowledge tasks and jobs. The model analyzes the knowledge tasks according to four basic knowledge processes: generation; codification; storage; and transfer. This taxonomy is used together with the distribution of productive work time of knowledge workers to ellaborate groups of knowledge tasks that are more suitable to be teleworked.

The objective of this study is to assess quantitatively how feasible blockchain is for various industries, such as logistics and supply chain, health, energy, finance, automotive, pharmaceutical and agriculture and food using a comprehensive list of indicators.

A decision aid was applied to the problem of identifying the feasibility of blockchain in Turkish industries. To this end, first, a set of indicators was identified. Then, the fuzzy AHP and fuzzy TOPSIS were utilized to assess the feasibility comparatively using the data gathered from a group of experts. Finally, a scenario analysis was conducted to ensure the consistency of our evaluation.

The findings of this study suggest that comparatively, logistics and supply chain, finance and health industries are the most feasible industries for blockchain. This study further suggests that blockchain is the least feasible for the automotive industry compared to the rest of the identified industries.

It is cumbersome to find out the respondents who have sufficient knowledge of both blockchain and the identified industries. Even if we took the utmost care in identifying the right respondents, we limited our search to the biggest industrial hubs of Turkey.

The findings of this research may help various decision-makers employed in governments, conglomerates, software and consulting firms and national research institutions make more informed decisions and allocate their resources more effectively.

To this date, the current studies have solely investigated possible research opportunities in blockchain and demonstrated several blockchain applications in stand-alone cases. To the best of our knowledge, however, no single study exists that evaluates the feasibility of blockchain comparatively and holistically among a group of industries using various indicators.

Consumption taxes are an integral part of government revenue in countries around the world and are often subject to consumer evasion. The rapid rise of electronic commerce has exacerbated this problem as cross-border selling over the internet has enabled foreign businesses to sell and avoid collection and remittance of tax on their sales.

In this paper, we search for the solution to this problem through the analysis of three tax collection models: vendor, financial institution, and internet service provider (ISP). In addition, we examine administrative tools that enable more effective collection as well as inducements for taxpayers or collection agents to carry out their responsibility.

We conclude that the ISP collection model is not feasible at this time. On the other hand, we find that the vendor model, when supplemented with appropriate administrative tools and inducements, and the financial institution model, both represent viable options for policymakers to consider.

Additive manufacturing (AM) is revolutionizing the manufacturing industry due to several advantages and capabilities, including use of rapid prototyping, fabrication of complex geometries, reduction of product development cycles and minimization of material waste. As metal AM becomes increasingly popular for aerospace and defense original equipment manufacturers (OEMs), a major barrier that remains is rapid qualification of components. Several potential defects (such as porosity, residual stress and microstructural inhomogeneity) occur during layer-by-layer processing. Current methods to qualify AM parts heavily rely on experimental testing, which is economically inefficient and technically insufficient to comprehensively evaluate components. Approaches for high fidelity qualification of AM parts are necessary.

This review summarizes the existing powder-based fusion computational models and their feasibility in AM processes through discrete aspects, including process and microstructure modeling.

Current progresses and challenges in high fidelity modeling of AM processes are presented.

Potential opportunities are discussed toward high-level assurance of AM component quality through a comprehensive computational tool.

The property standard index model was implemented as an interactive computer application to provide a decision support tool for the Queensland Department of Housing. The model was developed to assist housing managers evaluate the condition data collected on approximately 55,000 dwellings they manage. The collaborative nature of the project allowed design of the user interface to be consistent with other property information applications concurrently under development for Queensland Department of Housing and resulted in a prototype for a practical and use able decision support tool. This paper outlines the implementation of the model, the user interactions required and the final form of the prototype software.