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Security and safety have remained important concerns for mankind since ancient times. In the context of railways, however, the threat perceptions to safety and security have increased significantly lately. In view of this, the Indian Railways requires an effective and efficient security management system. The purpose of this paper is to propose an integrated approach to help develop the Indian railway security system (IRSS) by successively reducing the complexity of the system through a series of studies.

The relevant elements of the complex system of Indian Railways have been identified. The framework in which the elements exist and interact with each other has been clearly established using the interpretive structural modelling (ISM) technique. The output of ISM is further reduced in complexity by having different policy option profiles. A comparison of different option profiles has been done by a multi-criteria decision-making technique, the analytic hierarchy process (AHP), by choosing suitable criteria for comparison.

The following elements need to be pursued as the key objectives for making IRSS: protection of passengers, protection of property, modernisation, manpower enhancement, multi-skilling of staff, latest technology and enhanced legal powers.

The present research can be extended in many important ways. Interpretive structural models for different contextual relationships can be developed and used for formulating and implementing customised security policy. Policy elements and the ISM structure obtained in this research can be utilised for the system dynamic modelling of IRSS. A pilot study can be done to implement the recommendations made in this study.

The ISM model developed can be implemented as a policy tool in enhancing the railway’s security. Some of the policy elements proposed appear to be consistent with the strategic direction being undertaken in the railway security in the country.

Security is an important concern for mankind and social civilisations. The results have significant welfare implications in India and the rest of the world.

The present study is one of the first approaches in a series of studies in railway security in India. The results of this study can be extended to other security scenarios with similar needs.

The purpose of this paper is to address both the evolutionary and control aspects associated with the management of artificial superintelligence. Through empirical analysis, the authors examine the diffusion pattern of those high technologies that can be considered as forerunners to the adoption of artificial superintelligence (ASI).

The evolutionary perspective is divided into three parts, based on major developments in this area, namely, robotics, automation and artificial intelligence (AI). The authors then provide several dynamic models of the possible future evolution of superintelligence. These include diffusion modeling, predator–prey models and hostility models. The problem of control in superintelligence is reviewed next, where the authors discuss Asimov’s Laws and IEEE initiative. The authors also provide an empirical analysis of the application of diffusion modeling to three technologies from the industries of manufacturing, communication and energy, which can be considered as potential precursors to the evolution of the field of ASI. The authors conclude with a case study illustrating emerging solutions in the form of long-term social experiments to address the problem of control in superintelligence.

The results from the empirical analysis of the manufacturing, communication and energy sectors suggest that the technology diffusion model fits well with the data of robotics, telecom and solar installations till date. The results suggest a gradual diffusion process, like any other high technology. Thus, there appears to be no threat of “existential catastrophe” (Bostrom, 2014). The case study indicates that any future threat can be pre-empted by some long-term social measures.

This paper contributes to the emerging stream of artificial superintelligence. As humanity comes closer to grappling with the important question of the management and control of this technology for the future, it is important that modeling efforts be made to understand the extant perspective of the development of the high-technology diffusion. Presently, there are relatively few such efforts available in the literature.

Physical security has remained an important reason for, and the consequence of, societal living. In recent times, the threat potential and the risks of loss and damage due to criminal activities have increased substantially. In Indian Railways, it is being increasingly felt that efficient security management is inevitable for the development and sustainability of desired state of affairs. The purpose of this paper is to address the broad goal of achieving optimal strategies for minimizing security threats to Indian Railway Security System (IRSS).

The authors use two forecasting techniques, namely, Delphi technique and Harva method, whose joint approach allows the authors to use both quantifiable (Delphi technique) and linguistic (Harva method) data. The choice of the two approaches provides a multi-method approach to the research problem.

Predicted trend toward the expected scenario in 2020 has more or less matched with the actual developments for improvement in security scenario of Indian Railways. The positive indications are that there is an improving trend, which is expected to lead to a much better state of affairs with certain inputs.

The joint approach of Delphi technique and Harva method is a multi-method example of original research work in the railway security, which can also be implemented in other security settings, such as aviation or marine security. A replication of the exercise closer to the target date will throw light on the exact state of affairs in the area of railway security in India.

An outcome in consonance with the present exercise has been the implementation of the policy developed on the basis of the forecasts. Policy efforts initiated in the recent past have been consistent with the features discussed in the study. From the above indicators, it can be inferred that some of the policy initiatives taken are in line with the trend status as predicted by the Delphi exercise.

Security has been considered as an important reason, as well as a consequence, of living in a society. It has been perceived as the condition of being protected against danger or loss, and also refers to the freedom from exposure to danger (protection), implying a feeling of assurance against danger. Research work in this area, thus, has strong social welfare implications. This is particularly so as the area of security gained importance, not only in India, but also across the world.

The present study is the first of its kind in the area of railway security using systems approach. The approach used is quite generic and can also be implemented in other security settings, such as aviation or marine security.

The purpose of this paper is to identify the elements of education and training intervention that facilitate occupational transition intentions of undergraduates and encourage them to opt for entrepreneurial pursuit.

The study, conducted in India, employed the nominal group technique (NGT) – A systems science technique – which considers that users are experts and they must participate in the decision-making process. The application of NGT involved a workshop format; 15 domain experts participated in the workshop. Throughout the process, a democratic process was followed to avoid individual dominance and premature focusing on a single idea.

The study obtained 63 responses from experts for effective entrepreneurship education in India. The responses were reduced to seven elements after a few thematic iterations. These elements were then segregated into content (knowledge, skills and attitude) and learning interaction on the basis of experts’ responses. An initial draft of the course based upon the elements identified through NGT is presented in this paper.

This study is unique and different from previous research on entrepreneurship education in several ways: It takes cognizance of multiple stakeholders; It provides a theoretical framework along with empirical groundwork; It suggests curriculum contents that have contextual as well as universal relevance. This paper contributes to the emerging dimensions of entrepreneurship literature, which implies a shift from understanding a well-established Western context of entrepreneurship research to transitional societies from the East.

The purpose of this study is to identify the antecedents of entrepreneurial intentions of young women in India because currently Indian Government is emphasizing heavily on women’s participation in the mainstream of economic activities in the country. This study focuses on entrepreneurial intentions as the most important stage of entrepreneurship process. Based on the theory of planned behavior, propounded by Ajzen (1991), it points out intentions as the most significant predictor of human behavior.¤

This paper uses multi-method analysis for validation of the model proposed by Linan. In Study 1, an adapted version of Entrepreneurial Intention Questionnaire (EIQ) (Linan and Chen, 2009) was administered to a group of 248 female students studying in under-graduate science, commerce, arts or management courses, who voluntarily participated in the survey. Quantitative data analysis was conducted using partial least square (PLS) path-modeling algorithm. In Study 2, qualitative study was conducted on 110 young female students using focus group interview technique. Framework analysis was used for the data analysis of the qualitative study.

This study confirms the role of social valuation as an important antecedent of entrepreneurial intentions among women. However, it also identifies that entrepreneurship education is also an important element that affects the entrepreneurial intentions of young women in India.

The study uses multi-method analysis for identifying entrepreneurial intentions among young women in India.

The quest to acquire new customers and retain the existing ones is a challenge for all aviation companies. This paper attempts to assist the aviation companies in tackling this challenge by revealing the most important factors that their customers consider to be the most important while making purchasing choices.

Drawing on three separate studies, this paper identifies the most important factors that influence consumers' choice of airlines in an emerging economy context. The first study adopts a qualitative approach with 20 respondents (Max QDA is used for analyzing these data), followed by the second study based on a quantitative survey with 105 participants, and finally, the third study which employs a multi-criteria decision-making technique named fuzzy analytic hierarchy process (AHP) on a sample of 12 expert customers.

The findings of this paper reveal that customer care quality and on-time arrival are the two most important factors that aviation customers consider while making their purchase decisions. In contrast, baggage allowance and fastest route to destination are the two least considered by aviation customers while making their purchasing choices.

This study includes only a geographic-specific segment of passengers. Future studies of consumer preferences in the aviation industry may include consumers belonging to other geographic regions. Furthermore, future studies may segment their sample populations based on factors other than age, the purpose of travel and booking medium.

This investigation attempts to give a rich and holistic understanding of the different factors that influence the aviation choices of consumers of varying segments. This study has significant practical implications as modern-day airlines aim to optimally cater to the needs of their target segments without incurring additional costs on services that consumers do not deem to be as important.

This study highlights the importance attributed to each identified factor by passengers, something that previous research has mostly ignored.

Around the world, protecting environment and purchasing green products by the manufacturing firms progressively becomes a popular and important issue. Manufacturers are realizing the importance of producing green products under green practices. This study aims to propose an appraisement platform to evaluate the overall performance index of a firm under green practices. Furthermore, the study also helps in identifying ill-performing areas, which necessarily require future attention to augment green supply chain (GSC) of a firm. A case research is conducted to assess the real-life application by the proposed approach.

The authors used fuzzy performance index to measure the overall performance index of a firm. Beside this, they proposed a degree of similarity approach amalgamated with fuzzy performance importance index to classify the ills and strong indices in GSC extent.

The intermittent assessment of green practices and their metrics in the organizational supply chain management (SCM) is indeed necessary. The present study provides an appraisement module to assess overall GSC fuzzy performance index and also helps in identifying the ill-performing areas which require future augmentation toward successful green implementation.

The exposed research work dealt with chains of subjective indices (measure and their interrelated metrics), which are induced into hierarchical appraisement module. To tackle the uncertainty of indices, the subjective indices are transposed into interval-valued fuzzy number set (IVFNS), as IVFNs are preferred to undertake the uncertainty of GSC indices. The proposed approach is demonstrated with a case research to justify its validity and originality.

The purpose of this study is to design a DSS for construction sectors, which can determine the status of the related supplier alternatives, accompanying G-T, SC measures and their interrelated metrics. In today’s era, a supplier is observed as significant among entire agents of green supply chain (SC) management. Presently, it is determined that appraising worth of the supplier under green-traditional (G-T), SCs concerns still require the support of novel algorithmic/decision support systems (DSSs), which could embrace potential decision-making.

The authors have proposed a DSS (consisting of the implementation of multi-level multi-criterion decision-making [ML-MCDM], reference point approach [RPA] and multi-objective optimization on the basis of simple ratio analysis [MOOSRA] methods on constructed MCDM supplier evaluation appraisement module) for measuring the performance score of clay-brick suppliers coming under G-T SCs corresponding to fuzzy and non-fuzzy information. A comparative analysis is conducted among the performance scores against alternatives, obtained by the three methods, i.e. ML-MCDM, RPA and MOOSRA, for robustly making a potential decision.

The presented research offers a DSS toward managers of construction sectors for benchmarking the performance scores against supplier alternatives under G-T SC measures and their interrelated metrics, modeled by fuzzy cum non-fuzzy information.

Presented research work exhibited a DSS that can be used by construction sectors for benchmarking the supplier alternatives in accordance with their performance scores under G-T SCs. The MCDM G-T supplier evaluation appraisement module is constructed pertaining to small-scale clay-brick production units, located in the northern part of India to check the effectiveness of the proposed DSS.

The public distribution system (PDS) is an Indian food security system established to manage the distribution of food grains at affordable prices. As a result of the population explosion, the long-established PDS system finds it challenging to maintain operational efficiency, quality, trust and transparency. This paper explores the possibility of leveraging blockchain technology to overcome these operational hurdles.

Through a literature review and expert interactions, the present research identifies critical success factors in terms of enablers and barriers that influence the adoption of blockchain technology in PDS. Furthermore, we propose two independent interpretive structural models (ISM) and MICMAC to characterize these attributes.

The research identifies 15 distinct enablers and ten barriers that influence the diffusion of the latest technology in the sector at focus. The analyses disclose the interrelationships/dependencies among these enablers and between barriers, along with their individual driving power and dependence power.

The research showcases the importance of automating the system and illustrates how the features of blockchain technology can assist in augmenting stakeholder satisfaction levels. However, poor or nonexistent government regulations and patronage are found to be the major impediments to adoption. The research also delineates the cost implications of this barrier through its interrelationships with other barriers.

Interesting inferences are drawn from the models that offer actionable insights for the industry, government and technologists for improving PDS performance. Such interventions will ensure national food security through enhanced trust and transparency, which can further improve efficiency and effectiveness.