Modeling hazardous materials risks for different train make-up plans

This paper is concerned with the problem of how to place hazardous material cars in the train assembly process so that the overall derailment risk can be minimized. The approach considers both the probability of railway cars derailing en route by position as well as the risk associated with additional operations in the rail yard using recent US FRA data. The merits of this car placement model are illustrated through a case study of a railway corridor that connects Los Angeles (CA) to Chicago (IL). The case study demonstrates that the proposed risk minimization strategy could be implemented with minimal rail yard operation cost.     

Social Planner’s Solution for the Caspian Sea Conflict

This paper evaluates the proposed alternatives for sharing the Caspian Sea from the social planner’s or systems-level perspective with respect to the stakeholders’ utilities from the oil and natural gas resources of the sea. Different multi-criteria decision-making methods, namely dominance, maximin, lexicography, simple additive weighting, and TOPSIS are applied to determine the social planner’s ranking of these alternatives. Results suggest the Condominium governance regime as the most promising division method. Bankruptcy rules and cooperative game theory methods can be considered as the other socially optimal resolutions to the conflict over sharing the Caspian Sea energy resources among its five littoral countries. Consideration of these methods in negotiations may help with resolving the existing deadlock, which has been in place for two decades.     

Key factors affecting the hospital performance: a qualitative study using fuzzy logic

Identifying the key factors affecting the hospital performance helps better planning for hospital high performance. The purpose of this study is to provide a combination of qualitative and quantitative methods to investigate the hospital performance. In the qualitative section of this study, factors associated with hospital performance were detected using literature review, interviews, and expert panels. The findings analyzed by one sample t test and categorized by framework analysis method. In the quantitative section of this study, both direct and indirect relationships between factors were measured by using fuzzy Decision Making Trial and Evaluation Laboratory technique to detect influencing and influenced factors. Finally the key factors affecting the hospital performance were detected.     

Service quality aspects and sports scientific conventions: An experience from Iran

This study investigates the role of service quality aspects in a Sport Scientific Convention held in Mashhad, Iran in 2015. A sample of 175 conference attendees were targeted to investigate the quality of services offered, their satisfaction, and intention to return. However, the findings show that the quality of access to destination and venue affect service accessibility quality. The hotel value and hotel staff interaction affect accommodation quality, but the atmosphere of the hotel does not. The internal environment of the venue and its staff interaction affect venue quality in a direct and meaningful way, but venue value does not. In addition, convention process and product affect convention quality in a direct and meaningful way. There is also a direct and meaningful relationship between accommodation quality, venue, and convention quality, and service quality in the sports scientific convention. Access quality, however, is not a part of this relationship. On the other hand, there is a relationship between access quality and satisfaction, and satisfaction affects participants' intent to return to the convention.     

The impact of a STEM-based entrepreneurship program on the entrepreneurial intention of secondary school female students

Despite dedicated effort and research in the last two decades, the entrepreneurship field is still limited by little evidence-based knowledge of the impacts of entrepreneurship programs on the entrepreneurial intention of students in pre-university levels of study. Further, gender equity continues to be an issue in the entrepreneurial sector, particularly in STEM-focused entrepreneurship. In this context, this study was designed to explore the effects of a one-day female-focused STEM-based entrepreneurship program (for brevity, we call it the OzGirlsEntrepreneurship program) on the entrepreneurial intention of secondary school female students. The study collected data from two surveys completed by 193 secondary school female students, aged 14–16 years, who participated in the OzGirlsEntrepreneurship program. This program encouraged girls to develop and implement creative computational solutions to socially relevant problems, with an Internet of Things (IoT) component using the micro:bit device. The findings reveal that a key factor in the development of entrepreneurial attitudes in young female students is associated with soft-skills development, particularly in the areas of creative thinking, risk-taking, problem-solving, and leadership development. The importance of meaningful human connections, including positive role modelling and peer to peer learning were also important factors in fostering entrepreneurial intent. With these factors in mind, our findings highlight that the OzGirlsEntrepreneurship program substantially increased the entrepreneurial intention of secondary school female students. In addition, this study offers actionable implications and recommendations to develop and deliver entrepreneurship education programs for secondary school level students.

     

Developing a multiple-criteria decision analysis for green economy transition: a Canadian case study

ABSTRACT

Identifying planning strategies for the transition to a green economy is a formidable challenge. We proposed a novel multiple-criteria decision analysis model which can quantitatively identify the socio-economic and environmental impacts of various government and public policies. We applied the model to four practical scenarios in Canada for determining the optimal final demand that maximizes the country's GDP and employment while minimizing GHG emissions for small, short-term changes. As a result, the model suggested potential ways to simultaneously achieve a GDP growth of 2.5 billion CAD and creation of over 25,000 new jobs, and a saving of 2514 kt CO₂. As per the final demand, the electrification of domestic heating and transport should be more promoted. The proposed analysis tool will provide decision-makers with the ability to explore the design and effects of policy reforms, regulatory changes, and targeted public expenditure strategies, thereby overcoming barriers towards a green economy.     

Using the crowd for business model innovation: the case of Digikala

On November 15, 2015, Digikala, one of the largest online stores in the Middle East, launched its first-ever crowdsourcing contest called ‘A glance at tomorrow’. What distinguishes this contest from common crowd-based initiatives is that it was aimed at Business Model Innovation (BMI) rather than product and process innovation. Although using the crowd has proven to be an effective way for firms to boost their product and process innovation, its use for BMI is challenging. Based on real large-scale data from the Digikala’s crowdsourcing contest, this research focuses on the application of crowd-powered solutions in BMI, which has rarely been investigated previously. Our exploratory case study indicates that the crowd could contribute to the BMI process. Our findings point to a new form of ‘division of innovation labor’ in BMI. Contribution of the crowd in BMI is more likely to be relevant to Value Proposition and Value Delivery, while it might be less relevant to Value Capture and Value Creation. The results also support the notion that crowd-contributor characteristics affect the quality of proposals for BMI. We argue that this line of research could help companies design and implement customized crowd-based initiatives to better support their BMI process.     

The customer experience ecosystem in two cultural contexts

This study focuses on the development of a customer experience ecosystem during a journey which is embedded in meso- and macro-layers. Using the critical incident technique, the author collected in-depth interview data from bank customers in Switzerland and Iran to empirically study this ecosystem, including customer–company interaction in the micro-layer and social context of the meso-layer. Moreover, in a macro-layer analysis, the Hofstede cultural dimension was employed to show the role of cultural context in this ecosystem. The findings indicate that customer experience in the pre-encounter stage is mostly shaped by customer past experience and social context rather than company touchpoint. The importance of these factors is different in the two cultural contexts. Although customer experience in the encounter stage is mainly the result of customer and company interactions, other people have a role in this stage and cultural differences between the two countries largely explain these differences. Moreover, in the post-encounter stage, customers in different cultural contexts use various factors to evaluate their experiences and the effects on their emotional and behavioral responses. The findings provide key managerial implications for national and international companies with respect to the role of multiple layers in customer experience management.