Suchergebnisse

The realization of the need for sustainability as a result of soaring environmental issues has led many businesses, practitioners, and educationists to devise policies and practices which can save the earth from the harmful effects of human activities on the biophysical environment. One such set of activities identified by organizations is, "Going Green." This is, however, accompanied by many problems. One of those issues is the "adoption of green products by Customers." Thus, the research was conducted in this context to find the factors which play a significant role to consume green products in Southern Punjab, Pakistan. A comprehensive literature review was conducted to conceptualize a testable model showing the impact of attitude, aware and social context on green product consumption with "buying power" as a moderator. The target population for this study was taken as "earning hands of Southern Punjab". A sample size of 185 respondents retrieved using convenience sampling to answer the questions on an adapted structured questionnaire. Data were analyzed through regression and moderation analysis run in SPSS. The results of data analysis revealed that awareness, attitude, and social context have e significant positive impact on green product consumption. However, buying power was seen not to moderate the relationship of attitude, awareness, and Social Context on Consumption of Green products. The researcher suggests that marketers and government to run awareness campaigns and use promotion techniques for green product users to create social pressure on non-users and develop attitudes of people by developing environmental awareness and the need of environmental sustainability for human survival by going green.

The militia as an informal pro-government irregular force helps government forces through a range of asymmetric security threats. Since 9/11, the employment of militia forces has been on the rise. Although the informal Pro-Government Militias (PGMs) operate in juxtaposition with the regular land forces, they are loosely aligned with them. Given the nativity of its members to the battlefield, a militia is best suited to comprehend the operational and tactical situation and, making itself a viable option for state-led forces both from the perspective of low-cost force or its flexibility to deal with irregular threats. Most informal PGMs maintain a stronger ideological and political base, they do not often care about the limitation of their sponsoring state's sovereignty and the legitimacy of their actions. They may even develop linkages with the terrorist outfits for their immediate goals. This puts national security in grave danger. Given the risks, weaker states become vulnerable at the hands of their sponsored militants. Still, the state-led forces will remain inclined to exploit such paramilitary forces to let them shoulder the burden of national security against asymmetric threats.

European Union's Transport policy's pivotal aim is to strengthen the existing Transport infrastructure, which is crucial to economic development. The improvement in the transport sector should provide efficient logistics of goods, better travel and commuting facilities, and accessibility of the European region. This report, as part of the first phase of the Leveraging Big Data to Manage Transport Operations (LeMO) project, provides an introduction to big data in the transport sector. It identifies untapped opportunities and challenges and describes numerous data sources. This report is a part of WP1 which is a cornerstone of the LeMO project. It aims to generate a shared understanding of current big data landscape in transport and identifies a holistic view on opportunities, challenges, and limitations. The remainder of this report is structured as follows: Chapter 2 explores the characteristic of big data and highlights the big data challenges in the transport sector. It covers six transportation modes (air, rail, road, urban, water and multi-modal) and two transportation sectors (passenger and freight). Chapter 3 identifies several opportunities and challenges of big data in transportation, by using: several subject matter expert interviews, nineteen applied cases, and a literature review. It also indicates that the combination of different means and approaches will enhance the opportunities for successful big data services in the transport sector. Chapter 4 offers an intensive survey of the various data sources, data producers, and service providers. In addition, cartography was modeled to visualize data flows intuitively. Cartography demonstrates where data originated from and where it is flowing to. Chapter 5 summarizes all findings and provides a conclusion.

One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or "common good", covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to "classical" data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.