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.
Srivastava, A., Gaur, S., Swami, S. and Banwet, D. (2018), "Projecting futuristic scenarios for Indian Railway Security System (IRSS) using fuzzy dominance and contingency planning", Journal of Advances in Management Research, Vol. 15 No. 1, pp. 68-86. https://doi.org/10.1108/JAMR-05-2017-0056Download as .RIS
Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited
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 (Woellner and Dellancy, 1974). It also refers to the freedom from exposure to danger (protection), implying a feeling of assurance against danger. Another connotation of security implies the sense of the means of protection or defense (Stephenson, 1981). In India, particularly in the Indian Railway System (IRS), security and safety are two distinct areas of concern and are dealt with by two different departments of railways. Safety is a protection against hazards, while security is a protection against threats (Albrechtsen, 2003).
Traditionally, the defense forces of a country have been responsible for securing it from the acts of external aggression. However, the post-cold war developments have resulted in significant changes in fundamental military and security assumptions in the international context. For some countries, state-sponsored criminal activity has become a preferred form of low intensity conflict. Technological innovations such as internet, mobile communication devices, improvised explosive devises, sophisticated weaponry, and plastic money, etc. have made it easier for criminals to organize themselves and commit crime. As a result, the threat potential and the risks of loss and damage due to criminal activities have assumed alarming proportions.
To cause maximum damage and loss to the targeted country, criminals (especially, terrorists) have often shown a preference for crowded places (Dugdale-Pointon, 2005). Since handling of large numbers of passengers is an imperative requirement of the agencies involved in providing mass transportation services, such as Indian Railways, these setups appear as attractive targets. According to an audit report of the Comptroller and Auditor General (CAG) of India on Security Management in Indian Railways, “No security system can stop determined terrorists from attacking public places. Nevertheless, good security measures can make terrorist operations more difficult, increase the likelihood of being detected and identified, and keep casualties and disruptions to a minimum” (CAG, 2011-2012).
In such a scenario, a deliberate process of understanding risk and deciding upon and implementing actions to reduce risks to a definable as well as acceptable level is needed. The present paper attempts to focus on this issue at contingency planning level with a view to develop targeted futuristic scenarios for Indian Railways Security System (IRSS), and evaluating them using fuzzy dominance.
From a modest beginning with the commissioning of 34 km of railway line in the year 1853, the Indian Railways have risen to join the one billion ton freight loading club, which includes other significant railways worldwide, like the US, Chinese and Russian Railways. The number of passengers transported annually has also risen from 1,284 million in 1950-1951 to 8,397 million in 2013-2014 (Corporate Overview, 2014). The originating freight loading has increased by 75.85 percent in the year 2013-2014 to 1,058.81 million tons as compared to 602.12 million tons of freight loaded in the year 2004-2005 (Ministry of Railways (Railway Board), 2009).
In a highly networked set-up like that of Indian Railways, extending throughout India, the extent of complexity can be gauged by the sheer size of its infrastructure and operations. With 65,808 kilometers of route length, connecting 7,112 stations, IRS is the largest railway network under a single administration. With 12,617 passenger trains carrying over 22 million passengers per day, apart from 7,421 freight trains hauling over three million tons of freight traffic per day, it is one of the heaviest of transportation systems in the world (Gowda, 2014).
The core of the problem of security in Railways is the complexity of the system. Like in any large-scale system, complexity exists not only in the organizational structure and operational function of railways, but also in the relations and interactions of different elements of the system. Efforts have been made by the Government of India to study the security scenario and recommend measures for improvements in the security arrangements in Railways (icf.indianrailways.gov.in). However, terrorism and insurgency are continuing to affect internal security situation in the country (Patankar, 2008).
It is clear that there are challenges like size, existence of diverse conflict groups with vested interests and of a high degree of complexity, which are to be met in the IRSS. As also observed in the report of CAG (2011-2012), there are some gaps in the implementation of the integrated security scheme. These include gaps of resource allocation and utilization, lack of coordination between security agencies, lack of physical infrastructure, limited surveillance mechanism, inadequate communication facility, requirement of human resource training, lack of security consciousness amongst the traveling public, etc.
It is, therefore, required that contingency planning of security must be carried out in a systematic and holistic manner. Systems approach is a potent direction, which has earlier been applied for solving problems in complex large-scale domains (Department for Transport Research Report, 2005; Tierney et al., 2008). Forecasting trends, future scenarios, and futuristic predictions are important strategic components based on past knowledge and experience (Makridakis et al., 2010). An important aspect of scenario-based forecasting exercise is that it generates plausible scenarios, which can lead to advance contingency planning. The paper, therefore, attempts to utilize the power of Delphi technique and Harva method to develop scenarios to address the broad goal of achieving optimal strategies for minimizing security threats to IRSS through enhanced security management for the target year 2020, and attempts to develop action plan for the chosen most dominant scenario using fuzzy dominance.
The rest of the paper is organized as follows. Section 2 provides an overview of security management in railways. Section 3 delineates various methods of forecasting future scenarios. The next section provides the methodological details of the study. Section 5 presents the main results of the study. Section 6 provides status review of findings from the study. The last section provides conclusions and directions for future research.
2. Security management in railways
A nation’s enemies understand the vital role of transportation infrastructure and the human and economic damage that attacks upon it can wreak. Between 1995 and 2005, over 250 terrorist attacks worldwide targeted rail systems, resulting in more than 900 deaths and over 6,000 injuries (Riley, 2004). The ground transportation industry involves thousands of organizations in multiple transportation modes spanning both the public and private sectors. Then there is the sheer size of the transportation infrastructure, including endless miles of track, large numbers of bridges and tunnels, countless passenger stops, and a vast horde of trucks traversing the country day and night. Moreover, the system is designed to be open and accessible in nature.
The Department for Transport, UK (Department for Transport Research Report, 2005) commissioned a research study in October and November 2005 to look at how Londoners and users of the London underground railway responded to the attacks on the London public transport network in July 2005, and their attitudes to the potential introduction of higher security measures on the transport network. The results showed that a majority of respondents were not worried about traveling in London generally since the attacks, and that respondents agreed that the introduction of additional security measures on the London underground would greatly reduce the threat of a terrorist attack. Responses showed that respondents were generally positive about accepting some level of delay to allow for additional security. Several other research studies looked at the related aspects of this issue (Dft LUNR Research Report, 2005; Dft Research Report, 2006a, b, c).
Gao Xukuo and Wang Qiong (2013) have made a comparative study of different modes of transport using analytic hierarchy process, with criteria being “[…] five factors of the cost, speed, security, punctuality and transportation.” They have found rail transportation to be advantageous and suggested certain measures to remove the existing bottlenecks for further improvements.
It has been recognized by the industry experts that the ground transportation sector (in particular, railways) represents far greater security challenges than aviation (Greiper and Sauter, 2006). Endless miles of tracks being open and accessible in nature are also major features that enhance vulnerability to security threats of railway system. Various issues related to passenger rail security in the USA have been discussed in CRS (Peterman, 2005). Recently, Meyer (2012), combining insights from rational choice theory, crime prevention theory, and crime scripts, provides prioritization of protective security measures against explosive attacks on railways.
3. Forecasting future scenarios
Forecasting literally refers to prediction or estimation of future events. In management, forecasting becomes inevitable for long-term futuristic planning. The scenario building techniques fall under the broad field of “futures,” which has several other associated terms like futures research, futures studies, or futurology (Sardar, 2010). The term “futures” in plural here specifically refers to the possibility of the existence of many potential alternative futures, rather than simply a single future.
Voros (2001) mentions that there are three “laws” of futures, namely: the future is not predetermined, the future is not predictable, and future outcomes can be influenced by our choices in the present. Four classes of potential alternative futures (Henchey, 1978) have been defined: possible futures (those which we can possibly imagine), plausible futures (those which “could” happen), probable futures (those which are “likely to happen” based on continuance of current trends), and preferable futures (those which we “would like to” happen).
Seth (1996) provides varied interesting insights on the topic of futures. He mentions that, in futures studies, there has been an undue emphasis on technology forecasting, and that there should be a value-based socio-cultural outlook instead. This approach has been termed as “anticipatory management.” Seth emphasizes on futures consciousness, in which he argues that the elite in government and industry should become involved in the futures field, and that futurists must rise to the challenge of relating futures to the practical concerns and cultural backgrounds of a diversity of peoples.
3.1 Methodologies for forecasting future
Generally, five methods are used by scholars to look into the future (Narain and Gupta, 1989). They are: Delphi technique, trend extrapolation, scenario writing, mathematical models; and Harva method. These methods are briefly described below.
3.1.1 Delphi technique
The Delphi method was originally developed in 1950s by the RAND Corporation in Santa Monica, California. The Delphi method belongs to the subjective-intuitive methods of foresight. The name can be traced back to the Delphic Greek oracle (Woudenberg, 1991). This approach consists of a survey conducted in two or more rounds and provides the participants in the second round with the results of the first so that they can alter the original assessments, if deemed suitable in the light of group response. Alternatively, the participants might consider to retain their earlier opinion. There is no pressure on an individual participant as the survey is done anonymously. It is commonly assumed that the method makes better use of group interaction, when the questionnaire is the medium of interaction (Rowe et al., 2005). The Delphi method has been found especially useful for long-range forecasting (20-30 years), as expert opinions are the only source of information available.
Landeta (2006) provides a more recent review on the validity of the Delphi method in social sciences. As reviewed by Landeta (2006), at the end of the 1940s, researchers at the RAND Corporation (Santa Monica, California) started to investigate the scientific use of expert opinion. Studies were published on the superiority of group opinion over individual and on the justification of expert opinion in inexact sciences and its scientific use. During the recent years, the Delphi method has been used extensively for several complex forecasting problems. Several modifications and methodological improvements have also been made in this technique.
3.1.2 Trend extrapolation
This technique is used when forecasts have to be made in quantitative terms. To use this method, it is required that the forecaster should have some idea of the factors that have caused changes in the past; he should also have good grounds for believing that they will continue to influence developments similarly in the future (Narain and Gupta, 1989). Linear or curvilinear regression analysis and the Box-Jenkins method for time series analysis are the methods generally used for describing and projecting a trend. These methods can be used in combination with other methods.
3.1.3 Scenario writing
This is one of the main methods used for future studies. However, the term scenario may have different meanings. According to Schwartz (1991) and others, it may be used to denote a description of a hypothetical, likely or unlikely, development or situation, a development which is described as caused to some extent by the action and reaction of various factors, or a desirable or non-desirable development or situation. A scenario may also be a verbal description, with or without quantitative information. While writing scenarios, however, scholars have a number of methodological assumptions.
3.1.4 Mathematical model
This method is mainly concerned with quantifiable futures. It is considered more rigorous and scientific than other approaches. Mathematical models have been used extensively in the natural sciences (such as physics, biology, earth science, meteorology) and engineering disciplines (such as computer science, artificial intelligence), as well as in the social sciences (such as economics, psychology, sociology, political science). However, mathematical models make some underlying assumptions, which may not be tenable in long-run future scenarios.
In business and engineering, mathematical models may be used to maximize a certain output. The system under consideration will require certain inputs. The system relating inputs to outputs depends on other variables, such as decision variables, state variables, exogenous variables, and random variables. Depending on the context, an objective function is also known as an index of performance, as it is some measure of interest to the user.
3.1.5 Harva method
An added approach which has been used in some workshops on futurology in India is the Harva method. This is a modification of the method developed by the Swedish Education Association in cooperation with the Swedish Board of Education. Originally, the participants engaged to write about the future, were required to develop a negative picture, a neutral picture and an optimistic picture of the future. On this basis they prepared their own views of future society. This was the starting point of discussion. On the basis of these discussions, the participants developed a national picture. In the second stage the participants developed a “prognosis” picture and in the third stage, their task was to describe the “optative” picture of their own organization.
Harva method involves participation of domain experts in sub-groups to deliberate and discuss various aspects of the given system and to arrive at the current status, trend scenario, and the projection of future scenario for a target year. An extended method used in futurology studies in India is known as Seth-Harva method (Seth, 1996). It involves the following steps:
Step I – survey the present state-of-the-art of the issue under consideration.
Step II – develop a trend scenario for the target year chosen.
Step III – envisage the future as perceived by the expert group.
Step IV – develop a preferred future.
Step V – prepare an action plan based on the preferred future.
According to Fahey and Randall (1998), the concept of scenario development is generally commonly attributed to Herman Kahn during the 1950s at RAND Corporation. Kahn, a Military Strategist and Systems Theorist, encouraged people to “think the unthinkable,” first about the problem at hand and then about every manner of future condition (Bishop et al., 2007, p. 10). Kahn’s insights into the benefits of using scenarios planning found applications in military, politics, economics, and public policy. In 1970s, these techniques also found applications in the corporate world. Successful applications of the technique have been reported in the 1970s for organizations such as Royal Dutch Shell and the consulting firm SRI International (Fahey and Randall, 1998). Using these techniques, within two years, Shell moved from the eighth biggest oil company to the second in the world at that time (www.jiscinfonet.ac.uk/infokits/scenario-planning/evolution). A review of scenario planning literature appears in Chermack et al. (2001).
A recent application of Harva method can be found for group decision support system for public and private sector participation in New Delhi Expressway system in Madhuri and Saksena (2012).
3.2 Choice of methodology for forecasting future
The properties delineated of the above methods clearly indicate that the choice of the Delphi technique and Harva method was quite appropriate for the purposes of the current research. Both of these approaches are based on consensus building, are perceptual in nature, and use expert respondents. The techniques are particularly suited for complex systems, in which experts’ perceptual judgments are considered the best form of data to represent the current state of the system, and its long-range projection into the future. For similar reasons, the other techniques were not suited for the current study because of the reasons such as lack of concrete past data (for trend projection), complexity of the underlying problem (mathematical modeling), and the type of projection being required for a real-world problem (scenario writing). Further, the joint approach of Delphi technique and Harva method allows us to use both quantifiable (Delphi technique) and linguistic (Harva method) data to support our results. In this sense, the choice of the two approaches provides a multi-method approach to the research problem.
4. The study details
The operationalization of the current research was developed in three workshop settings. The first workshop, devoted to Delphi study, was conducted in continuation of an earlier workshop for content analysis. It was followed by the second workshop for the generation of alternative scenarios of IRSS. The alternative scenarios were compared in the third workshop by using the fuzzy evaluation technique. The methodological steps are described below.
4.1 Delphi technique
The Delphi technique is named after the Oracle at Delphi in Greek mythology, who used to predict the future. This technique integrates the judgment of experts by feeding back to each individual the estimate made by the other experts. The main characteristics of Delphi technique are as follows:
It is a repetitive process. The experts must be consulted at least twice on the same question, so that they can reconsider their answer, aided by the information they receive from the rest of the experts.
It maintains the anonymity of the participants. This is particularly so for their answers, as these go directly to the group coordinator. This means a group working process can be developed with experts who do not coincide in time or space and also aims to avoid the negative influence that could be exercised by factors in the individual answers in terms of the personality and status of the participating experts.
Controlled feedback. The exchange of information between the experts is not free but is carried out by means of a study group coordinator, so that all irrelevant information is eliminated.
Group statistical response. All the opinions form part of the final answer. The questions are formulated so that the answers can be processed quantitatively and statistically.
A preliminary requirement of Delphi technique is that a working group prepares a detailed questionnaire covering a wide range of related issues that may impact the objectives either directly or indirectly. The questions may be qualitative, or quantitative, or both. The questionnaire is responded to by the domain experts through a number of iterations each time with a different colored pen. Each iteration (after the first) is preceded by the display of aggregated results of the whole group of the previous iteration. Flexibility is provided to the respondent to change individual response of previous cycle on seeing the group response. The consensus usually emerges in two or three rounds.
The process of identifying elements for IRSS involved a workshop format organized for this purpose, in which 15 domain experts participated at the same physical location. The workshop was held in the year 2009 and was entitled Workshop on Security Management in Indian Railways from Systems Perspective (WSMIR). Domain experts belonged to IRSS, Indian Railway Administration, Academia and from amongst the users of IRS. The objective of the WSMIR workshop was broadly summarized as: to draw up an action plan outlining the optimal strategies for an enhanced security system in Indian Railways.
The results obtained after a content analysis exercise, in the form of lists of elements and dimensions, were provided as input to a core group of domain experts for Delphi study. After deliberations and discussions, a questionnaire was framed using 31 elements and their sub-elements (145) under nine dimensions. The Delphi Questionnaire (extracts shown in Figures 1 and 2) was administered to the entire group of domain experts. The results obtained were presented to the participants and the questionnaire was re-administered to allow them to rethink and respond accordingly. The responses to Delphi Questionnaire were analyzed for convergence after the second round and the outcome was analyzed systematically.
Thus, as a first question in the questionnaire, the respondents were asked to rate the various dimensions on a five-point scale in the three settings as given below:
current status (i.e. the current status in 2009 of security scenario in Indian Railways);
trend status for 2020 (i.e. the security scenario in 2020 with the existing level of security efforts); and
status achievable by 2020 with special efforts (i.e. the security scenario in 2020 with special and additional level of security efforts).
Subsequently, the respondents were asked to rate the various elements in each dimension on similar five-point scale in the three settings. This is shown for the first element of the first dimension in Figure 2.
4.2 Harva method
In the second workshop, the results of Delphi study were made available to the participants. They were asked to develop an action plan for enhanced security in Indian Railway System (ESIRS) for the target year 2020, taking 2009 as the base year. The entire group was divided into three sub-groups, namely, Team-A, Team-B and Team-C. Each group was asked to select its own leader.
Each group was requested to outline the present Indian Railway security status in India and the nation at large in the base year 2009 and to develop a trend scenario for the specified target year (2020) on the basis of the observations made regarding the base year (2009). They were also requested to identify two or three crisis points and two or three points of fulfillment in the base year. Each team was further asked to envisage a scenario of ESIRS (as it would emerge in the target year specified) as well as develop a preferred status of ESIRS by the Railway Administration within the railway system, and outside the railway system within the country based on their assessment.
Based on the future scenario, each group was requested to prepare an action plan for current decision, which, if implemented, may enable to fulfill the objective of safe and secure IRS. An additional action plan was synthesized by the entire group after presentations were made by the individual groups. Finally, in the third workshop, the scenarios generated were compared using the fuzzy evaluation technique.
In the following section, we present the results of the first workshop on Delphi study only at the dimensional level, as they have been reported in detail in Srivastava et al. (2015).The results of the other two workshops are presented in detail.
5.1 Outcome of Delphi exercise
The list of dimensions as per their ranking by experts in the year 2009 is presented in Table I. It is noticed that the average values for various dimensions, with special efforts for the target year (year 2020), are mostly around 4 (= Good). This implies that the experts envisage a scenario that ought to be good in respect of the status of IRSS. Highest average values are assigned to training, R&D and education (4.27, well above good mark) and modernization (4.27). This is indicative of the fact that training and modernization are considered as the most important prerequisites for improvement in IRSS.
It is also noteworthy that the lowest values have been assigned to social and cultural security (3.82) and inter-state security (3.90) indicating that even when the status of inputs like economy and finance, training, modernization, infrastructure, etc. are expected to be good or more, the internal security aspects are expected to be less than good. This issue was discussed with the experts, who explained that this is more realistic because the threats cannot be exhaustively visualized and the possibility of criminals breaching the security arrangements, once in a while, cannot be ruled out.
5.2 Outcome of scenario building exercise
The results of the Harva scenario building exercise are presented in Table II. The common thread running across the three scenarios is that the current status of IRSS is not up to the mark. The trend is toward improvement and the efforts being made are expected to lead to a better scenario in the year 2020. However, if the inputs in the form of broad features of action plan, as advised by the experts, are provided to IRSS, then the status of IRSS is likely to be even better and would be in the realm of preferred state of affairs.
5.3 Outcome of fuzzy dominance order evaluation of alternative scenarios for IRSS
It is difficult to judge a linguistically depicted scenario objectively, but qualitative evaluation appears to be a potent technique for the same. Fuzzy dominance evaluation of alternative scenarios has, therefore, been considered in order to ascertain which scenario is dominant on considered features to assess their implementability. Fuzzy dominance analysis has also been attempted for seven features, namely, feasibility (F-1), effectiveness (F-2), overall cost (F-3), reliability (F-4), technological advancement (F-5), scalability (F-6), and bureaucratic and political interference (F-7). These features were perceived as important characteristics of the considered dimensions by the domain experts.
In the context of IRSS, experts felt that effectiveness (F2) can be important for the social and cultural security (D1), feasibility (F1) for inter-state security (D4) and inter-border security (D5), overall cost (F-3) for economy and finance (D6), reliability (F-4) for collection and dissemination of intelligence (D2), technological advancement (F-5) for modernization (D3) and training R&D and education (D7), scalability (F-6) for human resources and infrastructure development (D8), and bureaucratic and political interference (F-7) for legal aspects and office procedures (D9).
The features, the sense in which they were used for evaluating the scenarios for better performance of IRSS, and the concerned dimensions are given in Table III.
Fuzzy opinion poll matrices were developed with the help of domain experts who were asked to give comparative statement for alternative scenarios of IRSS, that is, S-1, S-2, and S-3, for each of the features on linguistic variables denoted by alphabets as given below:
The order of the resultant comparison matrix is 7×3, 7 being the number of features and 3 being the number of alternatives. Since all domain experts participated in the fuzzy evaluation exercise, there were as many matrices as the number of experts. As per usual procedure, these matrices were quantified by mapping the linguistic variables on to the closed interval [0, 1]. Thus, A was mapped to 0.9, B to 0.7, C to 0.5, D to0.3, and E to 0.1.
After quantification, the average justified matrix was obtained by averaging out the cell entries of a feature. Table IV shows Quantified Fuzzy Mean Aggregate of Feature-Scenario Matrix and Table V shows the Dominance Matrix for Alternative Scenarios. Dominance matrix has been obtained from average quantified matrix by comparing the count of dominances on features for comparing one alternative scenario with another. The order of this matrix is, therefore, equal to the number of alternatives and hence it is a square matrix. The order of this matrix is 3.
Net dominance was obtained to determine which scenario dominates the other scenarios. The one which is most dominant gets the first rank. This scenario is then deleted from the dominance matrix in rows and columns, and the whole process is repeated for net dominance till all the alternatives are exhausted. It is clearly seen from the fuzzy mean values and the Dominance Matrix that the scenario visualized by Team-C, that is S-3, is the best scenario out of the three generated in the Harva scenario building exercise. However, it can also be inferred that the best scenario comes at a substantially higher cost. In case the funds are not commensurate with the requirements of Scenario-3, one of the other two scenarios could be preferred according to the availability of funds.
In view of the above concern, another policy alternative scenario, labeled S+, was designed by experts, which retained approximately all the criteria of S-3, but significantly improved upon on certain critical criteria such as effectiveness, overall cost and bureaucratic and political interference. The fuzzy mean aggregate values are shown in Table VI and the Fuzzy Dominance Matrix is shown in Table VII for alternatives scenarios S3 and S+. Table VI clearly indicates that S+ is better than or comparable to Scenario-3 in all aspects, including the overall cost and the negative impact of bureaucratic and political interference.
6. Findings from the study: a status review
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 status review of the salient dimensions, on which significant data is available in public domain, is provided below.
As per the experts, improvement toward modernization with better budgetary provision was an important trend to follow from 2009 onwards. Accordingly, as observed by the Standing Committee on Railways in its 12th Report to the 16th Lok Sabha (2016-17) on Safety and Security, computerized Railway Protection Force (RPF) Security Management System has been successfully implemented at 187 locations over Western and Central Railways and Security Control Rooms of RPF under pilot project. Roll-out phase amounting Rs. 21.99 crores has been approved and is under implementation. Security Helpline (No. 182) has been established at all Divisional Security Control Rooms of all Zonal Railways and it is functioning successfully in attending to distress calls from the passengers 24×7.
The Committee also reports that an integrated security system (ISS) is being implemented by the Railways to strengthen surveillance mechanism over sensitive stations of the Indian Railways. The system consists of IP-based CCTV surveillance system, access control, personal and baggage screening system and bomb detection and disposal system. The system is being implemented at an approved cost of Rs353 crore over 202 sensitive stations of the country. CCTV surveillance cameras have already been installed at 90 stations under ISS. Besides that, 113 baggage scanners, 206 door frame metal detectors, 997 hand held metal detectors and 40 block detectors items have so far been installed under ISS.
As per the submission of the Ministry of Railways to the Committee, a total of 344 railway stations of Indian Railways have been provided with CCTV cameras, which includes 94 stations where CCTV cameras have been installed under ISS. The Ministry of Railways has further proposed to install CCTV cameras at 983 stations under “Nirbhaya Fund.”
6.2 Human resource development, and social and cultural security
Regarding human resources, the developments in the Ministry of Railways have been in the expected direction. Almost all the senior officers of RPF have undergone Advanced Management Program in India and abroad at the leading institutes of national and international repute, and those remaining are being deputed gradually. In addition, officers are regularly deputed to attend various courses at leading management and police training institutes of India. As far as the other ranks of RPF are concerned, apart from providing training in use of modern weaponry and gadgets, the training syllabus has been redesigned to include modules on human rights, soft skills (including computer applications), unarmed combat, etc.
Security of women passengers is being given prime importance. The Ministry of Railways has decided to reserve at least 10 percent posts in RPF for women. All the ladies special trains running in metropolitan cities are being escorted by lady RPF constables. Ladies compartments in local trains are being escorted by RPF and GRP during peak/non-peak hours. In 2015, 126,938 male offenders were prosecuted under section 162 of the Railways Act, 1989 and fine of Rs 2.43 crore was realized. RPF is playing a leading role in rehabilitation of trafficked, run away and destitute children in coordination with Ministry of Home Affairs, Ministry of Women and Child Development and many NGOs under the campaign “Operation Muskaan-II” launched by Union Ministry of Home Affairs from 1 July, 2016 to 31 July, 2016, a total of 1,261 children including 18 trafficked children were rescued by RPF from railway premises and trains. Further, more than 8,500 run-away children were rescued by RPF in 2016 alone.
With the extensive use of social media platforms and applications on mobile telephones, especially Twitter, Whatsapp and other specially designed mobile phone applications, together with security helpline, a special kind of community participation has evolved. RPF has also intensified community involvement with its RPF Mitra Yojana. The Divisional Security Commissioners and Senior Divisional Security Commissioners of RPF at the divisional levels of railways have launched periodic awareness campaigns to apprise the passengers regarding dos and don’ts for ensuring their security. All these developments have resulted in a newer pattern of security and policing in the railways.
6.3 Inter-state and inter-border security, collection and dissemination of intelligence
As predicted, the coordination between RPF and intelligence agencies of the country has been improving. A dedicated post of DIG MAC (Multi Agency Center) has been created in the Ministry of Railways to remain in constant touch with the Ministry of Home Affairs for regular exchange of relevant information.
6.4 Training, R&D, and education
With the inception of a separate Directorate for RPF in RDSO, Lucknow, and the direction from the Director General, RPF, research and development activities in the field of passenger and freight security have been given due importance by the Ministry of Railways. The Minister of Railways has also announced setting up of a railway forensic facility for better investigation of cases of crime in railways. For better welfare of the Force, attention is being given to improve lodging and boarding facility for RPF personnel in the field. Regular meetings known as “Suraksha Sammelans” are being held for redressal of grievances of the staff at all levels.
7. Conclusions and future research
Both the forecasting exercises used in this work, Delphi and Harva scenario building, have revealed that the status of IRSS as in 2009 was not good enough. The positive indication was that the trend was for improvements, which was expected to lead to a much better state of affairs. However, the preferred status of IRSS requires certain inputs that would lead to the desired status of IRSS.
Delphi study revealed that the overall security scenario in IRSS was not really “Good.” It was likely to be “Good” by the year 2020 because of the existing ongoing efforts. However, in view of the nature of challenges to the railways, the experts prefer that the security scenario ought to be “Very Good,” for which systematically planned actions as brought out in this study are necessary. The Harva scenario building approach has resulted in the best scenario for IRSS, which does not simply emphasize increase in manpower, but a manpower that is multi-skilled and efficient. This is in contrast to the general current trend of having more manpower for better security. This significant finding can assist greatly in policy making. The features outlined in this study for evaluating alternative security scenarios may be considered, inter alia, for evaluating alternative policy options in other systems also.
The present research has been extended in several important ways. One obvious outcome of the exercise has been the implementation of the policy developed on the basis of the forecasts. Policy efforts initiated in the recent past have been in consonance with the features discussed in the study. From the above indicators, it can be inferred that some of the policy initiatives taken by the Ministry of Railways are in line with keeping the trend status as predicted by the Delphi exercise. Also, some of the policy indicators appear qualitatively in the contents of the three scenarios of the scenario building exercise. Further work in this area would throw light on the status of the relevant railway security parameters with this exercise conducted again in the year 2020.
Outcome of Delphi exercise – final round
|Current status 2009||Trend status for 2020||Status achievable by 2020 with special efforts|
|D1: social and cultural security||2.64||0.48||VIII||3.36||0.88||3.82||0.39|
|D2: collection and dissemination of intelligence||2.45||0.50||IX||3.36||0.64||4.00||0.60|
|D4: inter-state security||2.70||0.64||VII||3.20||0.98||3.90||0.70|
|D5: inter-border security||2.82||0.57||VI||3.27||0.86||4.09||0.67|
|D6: economy and finance||3.09||0.51||I||3.42||0.64||4.00||0.85|
|D7: training, R&D and education||3.00||0.74||III||3.55||0.50||4.27||0.75|
|D8: human resources and infrastructure development||3.00||0.60||IV||3.36||0.77||4.18||0.57|
|D9: legal aspects and office procedures||3.00||0.74||V||3.27||0.86||4.18||0.57|
Summary of the three scenarios derived from scenario building exercise
|Parameter||Scenario I (S1)||Scenario II (S2)||Scenario III (S3)|
Infrastructure – limited and traditional
Modernization – inadequate and no modern devices
Human resource – inadequate, less skilled and willed
Infrastructure – widespread but inadequate
Modernization – mixed scenario
Human resource – inadequate, less skilled and willed
Infrastructure – lacking
Modernization – priority toward technical upgradation
Human aspects – neglected, passenger satisfaction average
Others – slow response to crisis, poor civic awareness, crime (passengers, property. railway employees, poor analysis), intelligence set-up poor. Lack of coordination among security agencies (e.g. RPF, GRP and Civil Police)
infrastructure, modernization, human resource – same as above
Others – law and order problems, lack of socio-economic development, large population. increasing disparity, bureaucratic and political apathy; interaction and co-ordination lacking among various agencies. Other modes of transport not as developed and organized
Security given low priority by the Railway Administration and states
Railway administration in a state of inertia comparatively
National issues have direct, adverse impact on Railway security
Railway security agencies lacking in training for dealing with terrorism, etc.
Responsibility of security agencies has increased without commensurate increase in legal powers, manpower, etc
Image of the security agencies has improved → appreciated by passenger as well as Railway administration
Effective and efficient leadership in security agencies
Terrorism, extremism, communalism and regionalism major problems
General law and order grim
Lack of political will
Politicization of bureaucracy
Criminalization of politicians
Police politicized, ineffective
Public awareness increasing through Right to Information Act and media
Consumerism, economy growing – senior police officials trying to improve image and performance
|Crisis points||Lack of resources, mindset, poor base level, procedural delays, non-involvement of private sector in R&D, community apathy||Deterioration in law and order, increased public expectation, rise in crime – passenger, property and railway employees
Railway – commercial organization → Security low priority, financial crunch
Coordination – Average
Intelligence collection, collation and dissemination – weak
|Attitude for financial support quite negative
Security not treated as the major area of the concern
Corruption not coming down
|Points of fulfillment||Emphasis on modernization
Effective security in Railways
Moderate control of extremist activities
Growth of organization structure, process and behavior
|Improvement in training of manpower – specialized and capacity addition, modern weaponry, improved communication, transportation, computerization, surveillance.
increased public awareness toward railway security
|Integrated security system and composite security plan being implemented
Media activism, public awareness, judicial proactive role, Consumer Forums active
Improvement in areas of responsibility and performance
|Trends – 2020 (with continued present system)||Infrastructure – average progress
Modernization – good
Human resource – qualitative improvement
Intelligence – coordination and information quality will substantially improve
Legal limitations – average improvement
Finance – will substantially improve
Community participation – differential improvement
Training and R&D – will substantially improve
|10-15% improvement of the security in all respects
Better sharing of intelligence
Improved collection and dissemination of intelligence
Better infrastructure, training, weaponry, modernization, etc
Better integration of the RPF with the Railways
Enhancement of powers – legal
Better welfare of security forces personnel
|Trends – 2020 (as preferred by the group)||Infrastructure – above average progress (economic growth and policy of organization)
Modernization – very good
Human resource – substantial qualitative improvement
Intelligence – coordination and information quality will substantially improve
Legal limitations – better and updated laws
Finance – will substantially improve
Community participation Uniform improvement
Training and R&D – will substantially improve including behavioral aspects
Effective and efficient intelligence machinery
Improved coordination amongst various law enforcing agencies
Increased manpower and better trained manpower
Adequate budgetary provisions
Better research and development
New concept of policing
Welfare of security force personnel
High passenger satisfaction
Reduction in crime
Manpower re-deployment: No additional manpower
Modernization of equipment, machinery, weaponry, communication, transportation, surveillance
Enhancing training capacity
|Integrated and composite security plan implemented
Adequate legal powers
Training is commensurate with requirement of the job
Strength is as per the requirement
Morale and satisfaction level of all the stake holders is high
|Action plan||Adequate training
Modernization at all levels
Holistic security of Railway system
Enhanced community awareness and participation
Adequate availability of funds with freedom of choice in implementation
Clear role definition and legal empowerment justifying the role
|Various security agencies to co-exist in coordination
Increased security consciousness
Legal empowerment of RPF
Force multipliers – modern weaponry, faster communication, better transport, computerization
Strengthened intelligence machinery
Bring about attitudinal change
Improved R&D and intelligence analysis
Training and welfare schemes
Accountability for crime related lapses
Improve image of Railways
Deal strongly with the offenders without being discourteous to the passenger
Integration of the security agency (RPF) with the Railways → Complete integration
Features, sense of evaluation and concerned dimensions
|Feature||Sense of evaluation||Concerned dimension|
|Feasibility (F-1)||An increase in feasibility would give better performance of IRSS||Inter-state and inter-border security|
|Effectiveness (F-2)||An increase in effectiveness would increase performance of IRSS||Social and cultural security|
|Overall cost (F-3)||An increase in overall cost (budget allocation) should improve performance of IRSS||Economy and finance|
|Reliability (F-4)||An increase in reliability should increase performance of IRSS||Collection and dissemination of intelligence|
|Technological advancement (F-5)||An increase in technological advancement would increase performance of IRSS||Modernization, training R&D and education|
|Scalability (F-6)||An increase in scalability should improve the performance of IRSS||Human resources and infrastructure development|
|Bureaucratic and political interference (F-7)||A decrement in bureaucratic and political interference should improve the performance of IRSS||Legal aspects and office procedures|
Quantified fuzzy mean aggregated feature-scenario matrix
|Policy alternatives (scenarios)|
|7||Bureaucratic and political interference||0.50||0.51||0.89|
Dominance matrix for alternative scenarios
Quantified fuzzy mean aggregated matrix for the dominant and modified scenario
|Policy alternatives (scenarios)|
|7||Bureaucratic and political interference||0.89||0.62|
Fuzzy dominance matrix for alternative scenarios
Albrechtsen, E. (2003), “Security vs safety”, Department of Industrial Economics and Technology Management, NTNU – Norwegian University of Science and Technology, August, available at: www.foreignpolicy.com/articles/2011/02/22/it_takes_a_network (accessed July 17, 2014).
Bishop, P., Hines, A. and Collins, T. (2007), “The current state of scenario development: an overview of techniques”, Foresight, Vol. 9 No. 1, pp. 5-25.
CAG (2011-2012), “Report of the Comptroller and Auditor General of India (Railways)”, No. PA 14, available at: http://cag.gov.in/content/report-no-14-2011-performance-audit-security-management-indian-railways-union-government
Chermack, T.J., Lynham, S.A. and Ruona, W.E. (2001), “A review of scenario planning literature”, Futures Research Quarterly, Vol. 17 No. 2, pp. 7-32
Corporate Overview (2014), “Indian Railways”, available at: www.indianrailways.gov.in (accessed November 16, 2014).
Department for Transport Research Report (2005), “Research findings: attitude to transport security July 2005 London Bombings”, Department for Transport, London.
Dft LUNR Research Report (2005), “Summary report of the LUNR passenger screening trials”, Department for Transport, London.
Dft Research Report (2006a), “Security screening trial at Canary Wharf station”, Department for Transport, September.
Dft Research Report (2006b), “Security screening trial at Heathrow Express”, Department for Transport.
Dft Research Report (2006c), “Transport security measures: Sniffer Dogs trials (London and Brighton)”, Department for Transport.
Dugdale-Pointon, T.D.P. (2005), “Terrorist targets”, May 26, available at: www.historyofwar.org/articles/concepts_terrortargets.html (accessed November 16, 2016).
Fahey, L. and Randall, R.M. (1998), Learning from the Future: Competitive Foresight Scenarios, John Wiley & Sons, New York, NY.
Gowda, D.V.S. (2014), “Budget 2014-2015, speech of Minister of Railways”, July 8, available at: www.indianrailways.gov.in/railwayboard/uploads/directorate/finance_budget/2014-15_Final (accessed November 16, 2016).
Greiper, S. and Sauter, M. (2006), “Beyond aviation: the emerging ground transportation security market”, A Convergent Security Group Market Report, New York, NY, September.
Henchey, N. (1978), “Making sense of futures studies”, Alternatives, Vol. 7 No. 6, pp. 24-29.
Landeta, J. (2006), “Current validity of the delphi method in social sciences”, Technological Forecasting & Social Change, Vol. 73 No. 5, pp. 467-482.
Madhuri, M. and Saksena, P.K. (2012), “ANP-AHP supported group decision support system for public and private sector participation in New Delhi expressway system”, International Journal of Applied Information Systems, Vol. 1, February, pp. 4-10.
Makridakis, S., Hogarth, R.M. and Gaba, A. (2010), “Why forecasts fail. What to do instead”, MIT Sloan Management Review, Vol. 51 No. 2, p. 83.
Meyer, S. (2012), “Reducing harm from explosive attacks against railways”, Security Journal, Vol. 25 No. 4, pp. 309-325.
Ministry of Railways (Railway Board) (2009), Indian Railways Vision 2020, Government of India, New Delhi, December, available at: www.indianrailways.gov.in/indianrailways/VISION%202020_Eng_SUBMITTED%20TO%20PARLIAMENT.pdf
Narain, I. and Gupta, S.K. (1989), “India in the year AD 2000”, Mittal Publications, New Delhi.
Patankar, V.G. (2008), “Back to basics”, Force, January, New Delhi.
Peterman, D.R. (2005), “Passenger rail security: overview of issues”, Library of Congress, Congressional Research Service, Washington, DC.
Riley, J. (2004), “Terrorism and rail security, testimony presented to the Senate Commerce Science, and Transportation Committee”, RAND Co-corporation, Santa Monica, CA, March.
Rowe, G., Wright, G. and McColl, A. (2005), “Judgment change during Delphi-like procedures: the role of majority influence, expertise, and confidence”, Technological Forecasting and Social Change, Vol. 72 No. 4, pp. 377-399.
Sardar, Z. (2010), “The namesake: futures; futures studies; futurology; futuristic; foresight – what’s in a name?”, Futures, Vol. 42 No. 3, pp. 177-184.
Schwartz, P. (1991), The Art of Long View, Doubleday, New York, NY.
Seth, S. (1996), “Education is the key to the future”, Futures, Vol. 28 No. 6, pp. 672-675.
Srivastava, A., Swami, S. and Banwet, D.K. (2015), “Forecasting of security scenario in Indian Railways using Delphi technique”, working paper, Department of Management, DEI, Agra.
Stephenson, C. (1981), “Alternative international security systems: an introduction”, Peace and Change: A Journal of Peace Research, Vol. VII No. 4, pp. 1-6.
Tierney, M., Guharay, S.K., Colella, D., Jacyna, G., Barry, P., Koehler, M., Bergen-Hill, T. and Tivnan, B. (2008), “Systems engineering solution for technology deployment to combat complex threat scenarios in the homeland”, IEEE Conference on Technologies for Homeland Security, Waltham, MA, May 12-13, pp. 269-274.
Voros, J. (2001), “A primer on futures studies, foresight and the use of scenarios”, Foresight, Vol. 6 No. 1, pp. 1-7.
Woellner, G.W. and Dellancy, R.E. (1974), Elements of Transport, Butterworth, Oxford.
Woudenberg, F. (1991), “An evaluation of Delphi”, Technological Forecasting and Social Change, Vol. 40 No. 2, pp. 131-150.
Xukuo, G. and Qiong, W. (2013), “Research on the mode of present transportation in China and the analysis of railway transportation”, 6th International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII), Vol. 3, November 23-24, pp. 414-416.
Dft Research Report (2005), “Research findings: attitudes to transport security after July 2005 London bombings”, Department for Transport.
Disclaimer: the views expressed by the authors are based on a specific research study, and do not necessarily reflect those of Indian Railways Administration.
The authors are highly indebted to most revered Professor P.S. Satsangi Sahab, Chairman Advisory Committee on Education in Dayalbagh for Invaluable Guidance received from him. Profuse thanks are also due to Ranjit Sinha, the then Director General, Indian Railway Protection Force for the support provided by him. The authors acknowledge the support of Professor S.G. Deshmukh, Professor D.S. Mishra, and Professor C. Patvardhan for their valuable suggestions during the course of this work.
About the authors
Dr Anoop Srivastava is the Inspector General of Railway Protection Force with the Central Organisation for Railway Electrification at pan India level. He has wide experience in management of about 75,000 strong RPF as IG Administration and in crime control as IG Crime & Intelligence at the national level. He has also served as IG Railway Protection Special Force under the Ministry of Railways and as the Chief Security Commissioner of North Central Railway. He is credited with setting up an innovative system of security management in Konkan Railway Corporation Ltd., Navi Mumbai, India. He is the recipient of various awards and honours for professional excellence, including Director General’s Insignia and Indian Police Medal for meritorious service. He has a PhD in Management from Dayalbagh Educational Institute, Agra under MoU with ITD Delhi, MPhil from Punjab University, Chandigarh, PG Diploma in Public Administration from Indian Institute of Public Administration, New Delhi and MA and BA (Hon.) in Psychology from Bombay University, Mumbai, India. He has been associated as a Visiting Faculty with DEI, Agra, India. He has organized and also participated in a number of national and international conferences on Security, Transportation, Systems Science, Management and Consciousness, and received best paper awards on many occasions. He is a recipient of the Varshneya Award for contribution in Application of Systems Science to Security Management.
Sant Kumar Gaur is a Professor in Mechanical Engineering, Dayalbagh Educational Institute, Agra, Inida, with an experience of more than 25 years in research and teaching of UG and PG courses. He teaches Machine Design, Instrumentation, Entrepreneurship, Micro-Electro-Mechanical System and Rural Engineering. His areas of research interests are systems engineering, micro-electro-mechanical system, fuzzy sets and system, soft computing, intelligence system, interactive management, system dynamics, ergonomics, quantum computing and consciousness studies. He has authored several research papers with a significant impact factor which have been published in international and national journals. He has carried out a number of research projects funded by prestigious agencies like DST, CSIR, etc. He is a Life Member of several professional bodies like System Society of India, Indian Society of Continuing Engineering Education, etc. He has chaired sessions in various international and national conferences.
Sanjeev Swami is a Professor and the Head of the Department of Management, DEI, Agra, India. His PhD is in Business Administration from the UBC, Canada, MTech in Industrial Management from IIT Kanpur, and BE in Industrial Engineering from Allahabad. He has consulted international organizations like Pathe (Holland), EWW (USA), TERI and BHEL (India). He has been associated as the Faculty with UBC, Canada, IIT Kanpur, IIM Bangalore, IIITM, Gwalior, and Rotterdam School of Management. He has published several research papers in prestigious journals like Marketing Science, Interfaces, M&SOM, Marketing Letters, IJPE, Vikalpa, DEIJSER, AOR, JORS, and Journal of Cleaner Production. He has received career research awards by AICTE and DST, India. He has won Fellowships by American Marketing Association and UBC. His research contributions have been recognised in the form of Emerald Literati Network Awards, The European Marketing Academy (EMAC) and Elsevier Award, AIMS International Award, and an honourable mention as productive Indian management researchers in Economic Times.
Devinder Kumar Banwet, FIE, is a Professor Emeritus at IIT Delhi, a Founding Vice Chancellor of University of Engineering & Management (UEM) Kolkata, an ex-Head, Department of Management Studies, a Professor of HAG, and Dalmia Chair Professor as the Chairman of two inter-disciplinary programmes, ASRP and Entrepreneurship at IIT Delhi. He won a conferred PMI Distinguished Scholar Award 2016, Eminent Engineer Award 2011 of Indian Institution of Engineers Delhi Chapter, Fellow of the Institution of Engineers (India), Fellow of Indian Institute of Materials Management, Fellow of ISTD Pioneer Excellence Award as a doyen in SCM (2009), Dewang Mehta Business School Excellence Best Teacher Award, Emerald (UK) Literati Award, highly commended paper in the Journal of Enterprise Information Management Modelling and Systems (2011), and a Special PC Award for a joint paper at an International Transportation Conference at France. He was the President, Decision Sciences Institute USA India Chapter, Former National President of Indian Society for Training & Development (ISTD), and has held academic assignments at Kuwait Institute for Scientific Research, International Management Programme, University of Sorbonne at Paris and at Asian Institute of Technology at Bangkok.