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This paper studies the effectiveness of the bus priority lane (BPL) for public transport buses in the city of Bengaluru in India. We use the travel times on the BPL corridor as a measure of the effectiveness of the BPL. We find that there is a significant improvement in the travel times after the introduction of the BPL; for the worst 10% of the travel times, we find an improvement between 4% and 28%. Our methodology involves extracting trips on the BPL and computing the travel times for these trips from a time series of GPS information. Our methodology is scalable and can be used to compute the travel times between any two given points in other similar studies. We supplement our results with a novel test (called the D-test) for comparing the levels of stressful driving in the following scenarios: (a) morning peak hours (IST 07:00 h to 11:00 h) versus evening peak hours (IST 17:00 h to 21:00 h), and (b) northward trips versus southward trips on the BPL. We are able to infer that the drivers are generally more stressed during the morning peak hours and during the southward trips on the BPL. Partitioning the BPL into segments, we show that a majority of the segments exhibit similar effectiveness and driver stress trends as the full BPL stretch. We anticipate that corrective measures for the betterment of travel times and driver stress levels (e.g., introducing additional buses subject to vehicle re-balancing constraints, carefully planning the bus schedules to regulate bus traffic throughout the day, etc.) in some segments can lead to further improvements in travel times and reduction in driver stress levels. • Implementation of the Bus Priority Lane can reduce travel times. • Segmented analysis helps identify traffic bottlenecks for targeted intervention. • Driver-stress hot-spots can be identified for targeted intervention. • A novel statistical test compares driving stress levels across a pair of routes. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are among the most revolutionary breakthroughs by the context of decarbonization of road transport. The adoption of EVs has drawn increasing attention and is currently considered a potential route towards sustainable transportation. Businesses approaching the EV market must establish lucrative business models that overcome the adoption obstacles for EVs while assuring long-term growth. The intent of the current research exploration is to create a cutting-edge framework for EV enterprises that aims to maximize profit and save delivery time leading to high customer satisfaction. The volume discount strategy is used for profit escalation. The model presented in this paper is highly adaptable for a real-world problem as it incorporates uncertainty in the EV industry through generalized triangular neutrosophic numbers, an extension of fuzzy numbers. A modified version of the neutrosophic compromise programming approach is proposed in this paper. The results from this approach are validated using genetic algorithm. The proposed optimization-based framework is encapsulated in the form of study of a case from Bangalore city, in India. An in-depth exploration of two cases along with sensitivity analysis is carried out that helped in prioritizing some discrete customers and gave insights on which manufacturing site should be designated more focus. • Profit maximizing business model for electric vehicle (EV) merchants is proposed. • Uncertainty in EV industry is captured using fuzzy number. • A modified neutrosophic compromise programming technique is proposed. • Case study is considered involving particular case and sensitivity analysis. [ABSTRACT FROM AUTHOR]

Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of the day-to-day variability pertaining to the underlying complex equatorial and low latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using the Global Positioning System (GPS)-TEC observations (from 2009 to 2019) at Bengaluru (Geographic: 13.02° N, 77.57° E; Dip Angle: 13.77° N), a low latitude station in India. SSA has the most significant advantage of extracting information from the noisy time-series data with the first-four SSA modes in the decomposition, almost converging to total variance of about 99%. The proposed SSA-TEC model has been assessed by comparing it with the GPS-TEC observations as well as the outcomes from the latest version of the International Reference Ionosphere model (IRI-2016) and International GNSS Services Global Ionosphere Maps (IGS-GIM). The results demonstrate excellent outcomes with the Root Mean Square Error (RMSE) values between observed and model estimations laying at 1.58 TECU (SSA), 7.04 TECU (IRI-2016), and 8.89 TECU (GIM) with the respective correlation coefficients 0.99, 0.91, and 0.94. The model outcomes are in good agreement with the GPS-TEC observations, presenting relatively better estimates of TEC than the IRI-2016 and GIM during the geomagnetically quiet and disturbed daytime and nighttime conditions under different seasons and solar activity. Moreover, the proposed SSA-TEC model replicates the significant changes and time distribution characteristics of the ionosphere over the low latitude location, foreseeing the scopes for its regional implementation with a wide range of operations. • Ionospheric TEC model is proposed based on Singular Spectrum Analysis (SSA). • Model outcomes is assessed by comparing with the GPS-TEC, IRI and GIM estimations. • Excellent model outcomes are achieved with low RMSE and high correlations. • A decent agreement with GPS-TEC is seen even during geomagnetic storm conditions. • The outcomes suggest a regional model implementation for near-realtime operations. [ABSTRACT FROM AUTHOR]

Global Navigation satellite systems (GNSS) are predominantly affected by Ionospheric space weather. The GNSS signal delays due to ionospheric Total Electron Content (TEC) can be forecasted using advances in the emerging mathematics tools and algorithms. Machine learning algorithms such as Gaussian Process Regression (GPR) is considered in the present paper to implement in the forecasting of low-latitude ionospheric conditions. The GPS receiver data is obtained for 8 years (2009–2016) during 24th solar cycle from International GNSS Services (IGS) station located in Bengaluru (Geographical latitude: 12.97° N, Geographical longitude: 77.59° E), India. The performance of GPR model is validated using statistical parameters such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and correlation coefficient. The results of the proposed GPR model were compared with the Auto Regressive Moving Average (ARMA) model and Artificial Neural Networks (ANN) model during solar maximum period and descending phase of 24th solar cycle. The experiment results are evident that GPR model is significantly providing the promising results in forecasting the ionospheric time delays for GNSS signals. The outcome of the work can be useful to develop web based Ionospheric TEC forecasting system to alert the GNSS users. • The GPS-TEC variability is investigated during solar maximum period and descending phase of 24th solar cycle. • The performance of ARMA, ANN and GPR models are evaluated in forecasting the ionospheric delays for GPS signals. • GPR model has better predicted TEC than the existing ARMA and ANN models during geomagnetic quiet and storm periods. • Kernel-based approach of GPR model is well suitable to forecast the ionospheric TEC variations over low latitudes. [ABSTRACT FROM AUTHOR]

• We analyze route efficiency trade-offs emerging from combining pickups and deliveries in an urban distribution system. • We extend continuum approximation-based route length estimations by proposing adjustment factors for integrated pickup and delivery operations. • Local route efficiency can improve by up to 30%, while being highly sensitive to vehicle capacity and precedence constraints. • We apply our method to a real-world case study to inform the strategic design and operational planning of an urban distribution system. In this paper, we analyze the route efficiency trade-offs that emerge from combining first-mile pickup and last-mile delivery operations in an urban distribution system. We build on the extant literature on continuum approximation of optimal route distances and propose adjustment factors that account for the effects of integrated pickup and delivery operations. By means of comprehensive numerical experiments and regression analysis, we further propose a set of closed-form adjustment factors that improve existing continuum approximation-based route length estimations. These adjustment factors incorporate some non-trivial route efficiency trade-offs emerging from first-mile and last-mile integration that cannot easily be captured through continuum approximation. The proposed extensions are particularly relevant for the optimal strategic design and operational planning of large-scale, high-density last-mile distribution systems that are gaining in importance in light of e-commerce and omni-channel retailing. Our analyses suggest that the efficiency gains emerging from integrating first-mile pickup and last-mile delivery operations can be as high as 30%. However, the effective efficiency gains are sensitive to vehicle capacity constraints and other factors complicating the optimal stop sequence in integrated routes. We apply our proposed method to a real-world case study informed by operational data from one of India's largest e-commerce platforms for the city of Bengaluru. We find that by properly integrating its first-mile and last-mile operations, the company could reduce its urban traffic and emissions impact by up to 16%, while increasing the asset utilization and reducing the cost of operations of its vehicle fleet. [ABSTRACT FROM AUTHOR]

According to the United Nations Human Settlements Program (UNHSP), the number of slum households in developing countries continues to grow by a higher proportion as compared to its encompassing city. Traditionally, policy makers have concentrated on population control strategies by focussing on birth rates and rural–urban migration to stem the growth and emergence of slums. However, these strategies have often failed to achieve the desired results. In the present paper we find the key underlying processes that explains the observed differences in household life cycle between slum and non-slum households. We find that the slum households when compared to nonslum urban households, exhibit a large variation in the household size over the course of their life cycle, which in turn leads to inefficiency while building slum resettlement colonies. We have developed an agent based model, namely DynaSlum , to identify the key social determinants that impact the behaviour of a slum household. We use a novel and unique dataset based on the field work from 37 slums in Bangalore combined with the NFHS data to calibrate DynaSlum and validate our findings. This paper presents two major insights to address the challenges. First, we find that high rate of home leaving among young adults is the key determinants for the large variation in the life cycle of slum households. Second, we show that reducing home leaving among young adults will reduce the formation number of new slum households and contribute to a higher but stable household size. This will lead to efficiency and higher per capita resource consumption when building capacity for slum development (resettlement colonies) as policy makers would be able to plan for a stable household size. [ABSTRACT FROM AUTHOR]

The Indian IT services sector has grown from small beginnings at the bottom of value creation to a major player in the global information and communications technology (ICT) industry. It commands a 55% share in the global market for IT services. India's IT sector value proposition in terms of low cost with large supply of high quality talent is compelling. As a result, India has become the premier choice not only for outsourcing IT services by the developed-world's multinational corporations (MNCs) but also for locating their own Global In-house Centers (GICs), which simultaneously compete and partner with local firms. This gave rise to six additional clusters beyond the earliest, largest and robust cluster, Bangalore. The paper provides a review of relevant literature; develops a conceptual framework for evaluation of clusters; and presents data and analysis with respect to relative size, growth, specialization, MNC presence and connectivity to local firms through expatriates and returning Indians, ,innovation; and discusses adequacy of ICT infrastructure for future growth. Although there are clear signs that the Indian IT sector has been moving towards a regime of providing high-end value added services, the sector's value proposition – lower cost combined with a large supply of high quality talent – remains the single most compelling reason for the rise and growth of multiple export clusters. Thus the sector's growth appears to be a case of growth by replication rather than innovation. The paper concludes that the Indian IT sector's value proposition in terms of lower cost combined with large supply of high quality talent remains the single most compelling reason for the rise and growth of multiple IT services export clusters. While the old adage, “people follow jobs” still holds for large part of the labor force, there is little doubt that the sprawling IT services clusters in India - with more to come from Tier II and Tier III cities – indicate, in fact, that “jobs follow talent." Both local firms and the MNCs, through their GICs, are pushing the boundaries of location farther and farther to continue to leverage cost advantage and available pools of talent. [ABSTRACT FROM AUTHOR]

Public and private food consumption is responsible for significant environmental impacts, resulting in numerous studies that highlight the problem and reveal its magnitude at global and national scales. Drawing on a high level of data aggregation and focussing on individual choices and attitudes, current accounts stop short of grappling with the underlying complexity of the phenomenon. In this paper, we explore the conceptual value and methodological feasibility of linking Material Flow Analysis (MFA) and Social Practice Theory (SPT) to apprehend household food consumption dynamics. We develop and pilot a “Practice-extended MFA” framework among selected households in Bangalore, India. While MFA modelling serves to describe and quantify all food consumption processes and related flows at the micro-level, SPT is applied to investigate how individual, technological and sociological aspects of consumption practices converge towards household food “metabolic profiles”. The results revealed a complex system of interactions between food provisioning, storage and management practices, as well as socio-cultural norms. The paper concludes by emphasizing the contribution of a reflective stance between household metabolisms and consumption practices revealing not only what and how much food is consumed and wasted, but why and in what way. [ABSTRACT FROM AUTHOR]

Abstract: Rapid growth of the Information Technology (IT) sector in Bangalore, India, has transformed the city’s urban-industrial landscape since the liberalization of India''s economy in 1991. The city''s IT sector is closely integrated with a global system of production and caters largely to a global clientele. Apart from the impact of these developments on urban form, there are indications that they are causing uneven growth patterns and socio-economic polarization, which has resulted in different travel patterns in the work force. This paper compares the commuting patterns of employees in two types of firms, an IT multinational corporation and a traditional public-sector-unit (PSU), using data from a survey. Regression models show that there is a significant increase in travel cost as income rises for a sample of employees of the IT sector, even though travel distance is not influenced by income. The reverse holds true for a sample of employees of the PSU—rising income significantly increases distance though income does not affect travel cost. Behavioral choice models also show that with increasing income IT employees are more likely to choose two-wheelers and cars for commuting while PSU employees are more likely to choose public buses or walk to work. The paper suggests that Bangalore''s services-oriented IT economy is magnifying differences in work commuting patterns relative to those in the traditional manufacturing economy. The IT economy is also transforming travel behavior in terms of work travel mode choices among socio-economic groups. [Copyright &y& Elsevier]

Urbanisation and changing food habits in India have resulted in a shift in consumption from cereals to protein-based foods. Women play a major role in India in all activities related to food at household and therefore, the current paper reports the findings of the qualitative work conducted to understand women consumers' preference and perception towards meat and its attributes as a function of their awareness. The study collected the responses from 510 women residents of Metropolitan city of Bengaluru, India using questionnaires directly by face-to-face interviews and generated data on preference for fresh meat, purchase habits, value added meat products consumption, awareness about meat quality, and future expectations about meat sector. Findings from the current study indicate that, chicken is the most preferred meat (41.76%) while beef was least preferred (5.88%). The 40.59% of respondents preferred meat tenderness as an important eating quality followed by juiciness (37.06%) and flavor (12.94%). Consumers rated ritual slaughter, animal welfare and food safety as relevant issues in meat production, whereas regulations pertaining to meat production, processing of meat and food labelling were of minor significance. The study provide an insight into the significance of various consumer behaviour with respect to choice of meat, awareness on ritual slaughter, animal welfare and processing which is helpful in prioritizing future consumer research and policy decisions in India. [ABSTRACT FROM AUTHOR]

Abstract: Globalization and economic liberalization are enabling individuals in emerging economies like India to access lifestyles similar to the resource-intense West. This spread of consumerism poses substantial ecological challenges, and calls for studies that investigate the environmental values, ethics, and politics of India's new consumers. In this paper, I explore emerging pro-environmental behaviors in the city of Bangalore, India, among the new middle classes- its most significant consumer class. Using the case of home waste management, I show how household behavior change is made possible by neighborhood-based coordination, involving multiple actors such as environmentally-conscious residents, domestic help, and hired waste workers. Drawing on ecological citizenship theory, I discuss how waste management through recycling and composting is being implemented in Bangalore through networks of socio-economically privileged new middle class individuals. Their privileged social, political, and economic positions enable them to collectively enact changes in their cultural and structural contexts to facilitate pro-environmental initiatives. At the same time, the role of other actors like domestic servants and waste workers is also critical to the process. I show how ecological citizenship theory can be used to analyze and highlight voluntary involvement by socio-economically privileged individuals but fails to recognize the contributions of actors, who through their livelihood practices, play a pivotal role in producing the systems that enable pro-environmental behaviors among the elite. I conclude by suggesting that a critical analysis of the processes and political arrangements that produce pro-environmental behaviors is vital to sustainable consumption and production research in emerging economies like India. [Copyright &y& Elsevier]

The existence of slums or informal settlements is common to most cities of developing countries. In India, slums contain a wealth of diversity that is masked by a high level of poverty and insufficient access to resources. Recent studies have identified that it is important to assess the resilience of slums as they differ from one slum to another. While many slums are vulnerable to forced evictions, temporary jobs, and constant migration; few slums can respond and recover from external shocks and stress. In this paper, we investigate the resilience of slums based on novel field data from 37 slums in Bangalore. Specifically, we develop an agent-based model to understand how existing social, economic and environmental situation impacts the choices of slums. The paper makes two important findings. First, we find a high social satisfaction has a stabilizing effect, which means that despite more attractive economic opportunities, social satisfaction the slum dwellers derive from living in the neighbourhood of similar contacts is a strong motive to stay. However, given that a lack of economic opportunities causes a decline in the population, the social satisfaction will decrease as a function of the number of social contacts that move. We show that this cascading effect of emigrating population strongly depends on group identity such as religion. Second, we detect different regimes as social satisfaction increase, the population transitions from extinction to positive density dependence to density independence. Therefore, understanding the social capital of a slum community can offer insights into the ability of a slum to recover from external perturbations. • Understanding the resilience in slums. • Interplay of social, economic and environmental factors on the choices of slums. • Importance of social capital on the resilience of a slum. • Different regimes of slum population based on social satisfaction. • Approach to effective policy intervention in slums. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides a summary of an energy benchmarking study that uses performance data of a sample of Information Technology facilities in Bangalore. Information provided by the sample of occupiers was used to develop an Energy Performance Index (EPI) and an Annual Average hourly Energy Performance Index (AAhEPI), which takes into account the variations in operation hours and days for these facilities. The EPI and AAhEPI were modelled to identify the factors that influence energy efficiency. Employment density, size of facility, operating hours per week, type of chiller and age of facility were found to be significant factors in regression models with EPI and AAhEPI as dependent variables. Employment density, size of facility and operating hours per week were standardised and used in a separate regression analysis. Parameter estimates from this regression were used to normalize the EPI and AAhEPI for variance in the independent variables. Three benchmark ranges – the bottom third, middle third and top third – were developed for the two normalised indices. The normalised EPI and AAhEPI of LEED rated building, which were also part of the sample, indicate that, on average, LEED rated buildings outperform the other buildings. [ABSTRACT FROM AUTHOR]

Abstract: The literature on world cities and global cities has a resilient tendency to list hierarchies based on, among other things, the ability of a city to act as a command and control centre of the forces of globalization. This implies, even if it is not always explicitly acknowledged, there are other cities in the process of globalization that provide the resources that are commanded and controlled. There is also a wider recognition today that the process following the fundamental changes in technology since the 1980s, despite all its significance and unique features, is only the latest phase in the historical process of globalisation. Our understanding of resource cities could then begin by identifying the features of such a city that is common to all its phases of globalization. This paper looks at the experience of the south Indian city of Bangalore with three phases of its globalization: the colonial phase, the garment phase and the information technology phase. It finds that even as a resource city like Bangalore uses some of its unique characteristics to attract the attention of the command and control centres of each phase of globalization, it requires state support to do so effectively. Since the demands of each phase of globalization are very different, it needs to create new peripheries to provide the resources the command and control centres require. This has its implications for place as the peripheries can become more dominant than the city centre in economic and other terms. [Copyright &y& Elsevier]

Abstract: The Government of India has sought to improve air quality through fuel quality improvements and tightening of vehicle emission norms to control vehicular air pollution in urban areas. Air quality nevertheless continues to be an area of concern in most urban areas of India as a result of the rapid increase in the number of registered vehicles. This paper discusses the various fuel quality and vehicular technology improvements that have been taken up nationally, and in Bangalore City, and also traces the air quality trend monitored at an important traffic junction in Bangalore over 10-years. The analysis shows that particulate matter and sulphur dioxide concentrations have decreased and correspond to the incremental fuel quality and vehicle emission norms implemented during the period but particulate matter and respirable suspended particulate matter concentrations are still above permissible standards. [Copyright &y& Elsevier]

Bangalore is one of the fastest growing cities in India and is branded as ‘Silicon Valley of India’ for heralding and spearheading the growth of Information Technology (IT) based industries in the country. With the advent and growth of IT industry, as well as numerous industries in other sectors and the onset of economic liberalisation since the early 1990s, Bangalore has taken lead in service-based industries fuelling substantial growth of the city both economically and spatially. Bangalore has become a cosmopolitan city attracting people and business alike, within and across nations. This profile notes the urban setting and provides an overview of the urban fabric, while discussing various prospects related to infrastructure and governance. This paper also outlines the challenges in planning to ensure better delivery of basic services across the city. [Copyright &y& Elsevier]

This study examines the process of restructuring taking place in metropolitan cities in India. The opening up of the Indian economy since 1991 has brought much change in large cities. Both local and global agencies have played a role but with considerable variation in different states of the country. Taking the case of Bangalore (Karnataka) and Kolkata (West Bengal), the objective of this paper is to examine these agencies and their impacts on the cities’ growth policies. As an early leader of the reform process, Karnataka state and Bangalore, its capital, provide a contrast to West Bengal and its capital, Kolkata. The sub-national comparative study undertaken here could have wider applicability to other large developing countries. [Copyright &y& Elsevier]