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Taxi services have evolved with the growth of information communication services and have become an essential infrastructure in a city’s transport landscape. In today’s era, mobility has become a vital need for people as they contemplate how to accomplish specific tasks, which require travel, time, and distance. Taxi services have filled this void by allowing people to commute to the last mile and meet their daily requirements. Failure of cab service operators to offer affordable and reliable taxi service would result in inferior taxi services that lead to dissatisfaction among customers. The key objective of this research was to determine important factors, namely, socioeconomic and service attribute factors that influence people’s choice based on satisfaction levels in selecting a particular taxi service like Ola and Uber in Bhubaneswar city. The study found that socioeconomic and service attribute factors were important in determining the choice of taxi service. Furthermore, it also revealed that people were more sensitive to the reliability of taxi service and cost in comparison to the quality of service and driver’s behavior. The study results would help cab service providers in customizing their services to attract more customers and increase their market share.

The foot-and-mouth disease virus (FMDV) causes a highly infectious disease of all cloven-footed animals. The RNA genome of the virus continuously evolves, leading to the generation of new strains; this necessitates the selection of new vaccine strains to ensure complete protection. Infection with one FMDV serotype does not provide cross-protection against the other FMDV serotypes. Many of the recovered animals may become carriers of the FMDV, but they still remain susceptible to the other serotypes. Coinfection with multiple FMDV serotypes has been reported and studied to understand the virus evolution. Isolation and characterization of all the involved serotypes in the mixed infection case is essential to understand the molecular evolution of the virus. In this study, two cases of coinfection were studied by selective isolation of each of the FMDV serotypes under the cross-serotype-specific immune pressure. It was estimated that the virus present in a minimum of 10−0.92TCID50could be isolated from the mixed population containing other serotypes in infective doses of 100.25TCID50or less. All involved serotypes present in the mixed infection cases were isolated, without any cross-contamination. Virus characterization revealed that genotype 2 was of serotype A virus from a sample collected in 1995, which was last reported in 1986, indicating a possible subdued prevalence of the genetic group even after vanishing from the field.

Demand for poultry meat and eggs is increasing at a faster pace due to its good quality, nutritive values, and reasonable price. With the growing demand for egg and poultry meat, the demand for poultry feed is also increasing. Most of the feed ingredients which are used in poultry feed are also used for human nutrition. So these major feed ingredients and cumulatively poultry feed are facing market competition with increased cost. This study proposed linear programming (LP) technique to minimize the feed cost for small scale poultry farms. It employs locally available feed ingredients to formulate the broiler starter and finisher feed mix. The dietary nutrient requirement for broiler starter and finisher stage were determined from the prescribed standard specifications by Indian standard institutes and National Research Centers, Indian Council of Agricultural Research (ICAR). Sixteen feed ingredients were selected to formulate the optimal feed mix to minimize the total cost of feed mix subject to the essential nutrient constraints. Microsoft excel solver was used for the formulation of liner programming model and optimal feed mix for broiler starter and finisher were obtained.

Indian thermal power industries, being perceived as the most polluting, are experiencing tremendous pressure to implement sustainable supply chain practices. In this light, the purpose of this article is to explore the factors that initiate sustainable supply chain management (SSCM) adoption in Indian thermal power industries and understand the interrelationship existing among them. Interpretive structural modeling (ISM) technique is employed to extract the structural relationship existing among the SSCM enablers and portray the same through a hierarchical model. Further, MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement) analysis has been employed to classify the enablers by taking their driving and dependence power as a measure. Eleven SSCM enablers have been explored through an extensive review of the literature. The interpretive structural model of selected enablers indicates that SSCM adoption in thermal power plants is mainly due to “pressure from environmental advocacy groups” and “government policies and employee pressure”. Prior knowledge of these influential factors and their interdependence will help the decision makers to develop suitable strategies that would enable the organizations to reduce the impact of barriers while optimizing the benefits derived from the enablers.

The explosion of the population in India has put a tremendous pressure to generate huge amount of energy, particularly electrical energy. Indeed, more than 50% of the total electrical energy produced in the country is generated by the coal based thermal power plants and is expected to be continued for another 2-3 decades. Growing concern over the environmental effects caused by the supply chain activities of the power industries that affects ecosystems and quality of life adversely as well natural resource depletion has been drawing attention of organisations to focus on sustainability practices. Realising the importance of sustainable practices in traditional supply chain management, an effort has been made to develop a framework by using AHP TOPSIS to study SSCM strategies. The findings of the research will facilitate the analysis and assessment of managerial approaches for SSCM in power generation facilities with its differing aspects rather than few limited aspects.

In an attempt to satisfy its ever increasing need for energy, the Indian government has setup a large number of coal fired power plants, which in turn has led to increased socio-environmental hazards such as global warming, acid rain, scarcity of drinking water, reduced crop production, and a stressful work environment. Realising the fact, efforts have been made by government, industry as well, as by the academicians to develop and incorporate sustainable practices in the thermal power supply chains. However, sustainable supply chain management (SSCM) implementation is a complex activity owing to its dependence on various factors with a varying degree of influence on SSCM. In light of this, this research has been carried out to explore and evaluate the degree of influence of the factors those that influence SSCM either positively or negatively. It was observed that academic involvement and lack of coordination are the most significant driver and barrier respectively. Knowledge of the influential factors and their ranks will help the decision makers in reducing the impact of the barriers and optimise the benefits derived from the drivers.

Green supply chain management (GSCM) focuses on reduction of the adverse impacts of supply chain activities as well as a minimisation of energy and material usage. A successful implementation of GSCM is important for industries to increase economic-environmental performances. However, the GSCM adoption rate in Indian companies, particularly in the mining sector is not encouraging. There exists a set of factors that enhances GSCM adoption while others offer resistance to it. An attempt has been made to empirically test the relationship of various factors on GSCM implementation considering data collected from 144 respondents working in Indian mining industries, in which it was found that there is no difference in perception regarding the barriers of GSCM implementation. GSCM adoption in mining industries is initiated by factors like: 'society pressure', 'regulative pressure', 'investors' pressure' and 'eco-literacy among supply chain partners'. Further, practices like 'organising', 'initial environmental review' and 'continuous improvement' enhance GSCM effectiveness.

A simple, rapid and sensitive diagnostic assay for Foot-and-mouth disease (FMD) is required for deployment in the field. In this study, development of Reverse Transcription-Loop Mediated Isothermal Amplification (RT-LAMP) assay based on the 3D polymerase gene for specific and rapid detection FMD virus (FMDV) was carried out. The assay was optimised with viral RNA extracted from serotype O, A and Asia 1 FMDV vaccine strains, which resulted a reliable amplification at 65 °C for 60 min. The amplified RT-LAMP products were identified by agarose gel electrophoresis with ethidium bromide staining or observation by naked eye for the presence of turbidity and colour change following the addition of hydroxyl naphthol blue (HNB). The specificity of the assay was demonstrated by the absence of amplification of genome extracted from other viruses or cellular origin. With respect to analytical sensitivity the developed RT-LAMP assay was found more sensitive than routinely used multiplex PCR (mPCR). Further, the assay was evaluated with RNA extracted from cell cultured isolates (n= 50), tongue epithelial samples (n= 150) and semen samples from infected bulls (n= 13). In conclusion, RT-LAMP with HNB dye was shown to be simple, specific and sensitive assay for rapid diagnosis of FMDV infection. Further, the assay has the potential for field deployment and use for rapid FMDV surveillance in India.