Collection and integration of local knowledge and experience through a collective spatial analysis

This article discusses the convenience of adopting an approach of Collective Spatial Analysis in the P/PGIS processes, with the aim of improving the collection and integration of knowledge and local expertise in decision-making, mainly in the fields of planning and adopting territorial policies. Based on empirical evidence, as a result of the review of scientific articles from the Web of Science database, in which it is displayed how the knowledge and experience of people involved in decision-making supported by P/PGIS are collected and used, a prototype of a WEB-GSDSS application has been developed. This prototype allows a group of people to participate anonymously, in an asynchronous and distributed way, in a decision-making process to locate goods, services, or events through the convergence of their views. Via this application, two case studies for planning services in districts of Ecuador and Italy were carried out. Early results suggest that in P/PGIS local and external actors contribute their knowledge and experience to generate information that afterwards is integrated and analysed in the decision-making process. On the other hand, in a Collective Spatial Analysis, these actors analyse and generate information in conjunction with their knowledge and experience during the process of decision-making. We conclude that, although the Collective Spatial Analysis approach presented is in a subjective and initial stage, it does drive improvements in the collection and integration of knowledge and local experience, foremost among them is an interdisciplinary geo-consensusPeer ReviewedPostprint (published version

Third Revolution Digital Technology in Disaster Early Warning

Networking societies with electronic based technologies can change social morphology, where key social structures and activities are organized around electronically processed information networks. The application of information and communications technologies (ICT) has been shown to have a positive impact across the emergency or disaster lifecycle. For example, utility of mobile, internet and social network technology, commercial and amateur radio networks, television and video networks and open access technologies for processing data and distributing information can be highlighted. Early warning is the key function during an emergency. Early warning system is an interrelated set of hazard warning, risk assessment, communication and preparedness activities that enable individuals, communities, businesses and others to take timely action to reduce their risks. Third revolution digital technology with semantic features such as standard protocols can facilitate standard data exchange therefore proactive decision making. As a result, people belong to any given hierarchy can access the information simultaneously and make decisions on their own challenging the traditional power relations. Within this context, this paper attempts to explore the use of third revolution digital technology for improving early warning

Assessing Devolution in the Canadian North: A Case Study of the Yukon Territory

Despite a rich literature on the political and constitutional development of the Canadian territorial North, few scholars have examined the post-devolution environment in Yukon. This lacuna is surprising since devolution is frequently cited as being crucial to the well-being of Northerners, leading both the Government of Nunavut and the Government of the Northwest Territories to lobby the federal government to devolve lands and resources to them. This paper provides an updated historical account of devolution in Yukon and assesses its impact on the territory since 2003. Relying mainly on written resources and 16 interviews with Aboriginal, government, and industry officials in the territory, it highlights some broad effects of devolution and specifically analyzes the processes of obtaining permits for land use and mining. Our findings suggest that devolution has generally had a positive effect on the territory, and in particular has led to more efficient and responsive land use and mining permit processes

Consumer decision making in mobile-banking service selection

This paper reports on the findings of a study of 267 consumers on the first order selection criteria within a decision making model that utilizes the Analytic Hierarchy Process (AHP) to evaluate mobile banking service selection. The AHP analysis of the first order selection criteria for the full data sample identified ‘Time Saving’ as the highest ranked factor followed by ‘Control’ then ‘Any Place’ and lastly ‘Cost’. The survey also reports on consumer usage patterns for internet and mobile services as well as exploring their experiences with mobile banking services

What Europe Knows and Thinks About Algorithms Results of a Representative Survey. Bertelsmann Stiftung eupinions February 2019

We live in an algorithmic world. Day by day, each of us is affected by decisions that algorithms make for and about us – generally without us being aware of or consciously perceiving this. Personalized advertisements in social media, the invitation to a job interview, the assessment of our creditworthiness – in all these cases, algorithms already play a significant role – and their importance is growing, day by day. The algorithmic revolution in our daily lives undoubtedly brings with it great opportunities. Algorithms are masters at handling complexity. They can manage huge amounts of data quickly and efficiently, processing it consistently every time. Where humans reach their cognitive limits, find themselves making decisions influenced by the day’s events or feelings, or let themselves be influenced by existing prejudices, algorithmic systems can be used to benefit society. For example, according to a study by the Expert Council of German Foundations on Integration and Migration, automotive mechatronic engineers with Turkish names must submit about 50 percent more applications than candidates with German names before being invited to an in-person job interview (Schneider, Yemane and Weinmann 2014). If an algorithm were to make this decision, such discrimination could be prevented. However, automated decisions also carry significant risks: Algorithms can reproduce existing societal discrimination and reinforce social inequality, for example, if computers, using historical data as a basis, identify the male gender as a labor-market success factor, and thus systematically discard job applications from woman, as recently took place at Amazon (Nickel 2018)

MCDM Farm System Analysis for Public Management of Irrigated Agriculture

In this paper we present a methodology within the multi-criteria paradigm to assist policy decision-making on water management for irrigation. In order to predict farmers' response to policy changes a separate multi-attribute utility function for each homogeneous group, attained applying cluster analysis, is elicited. The results of several empirical applications of this methodology suggest an improvement of the ability to simulate farmers' decision-making process compared to other approaches. Once the utility functions are obtained the policy maker can evaluate the differential impacts on each cluster and the overall impacts in the area of study (i.e. a river basin) by aggregation. On the empirical side, the authors present some studies for different policy instruments including water pricing, water markets, modernization of irrigation systems and a combination of them.multi-attribute utility theory, water management, irrigation, policy analysis, Agricultural and Food Policy, Q25, Q15, C61,

Current policy issues in the governance of the European patent system

The European Parliament has been working towards building a discussion platform and a resource for further policy actions in the field of intellectual property rights. The Science and Technology Options Assessment Panel has set the goal of further enlarging the area of investigation in light of recent policy developments at the European level. In particular, the current study covers current policy issues in the governance of the European patent system, such as the backlog issue, the enhancement of patent awareness within the European Parliament, patent enforcement, the regional dimension of intellectual property in Europe, patents and standardisation, the use of existing patents, and patents and competition. These issues were discussed in the conference with stakeholders from European to national patent offices, from private to public sector actors. As a result of the conference, it was stated the need for an IP strategy for Europ

How do top- and bottom-performing companies differ in using business analytics?

Purpose Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA. Design/methodology/approach Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies. Findings Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment. Practical implications Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities. Originality/value This study provides useful management insights into the effective use of BA for improving organizational performance