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Enabling the Business of Agriculture 2019 presents indicators that measure the laws, regulations and bureaucratic processes that affect farmers in 101 countries. The study covers eight thematic areas: supplying seed, registering fertilizer, securing water, registering machinery, sustaining livestock, protecting plant health, trading food and accessing finance. The report highlights global best performers and countries that made the most significant regulatory improvements in support of farmers.

Enabling the Business of Agriculture (EBA) 2017, the third report in the EBA series, offers insights into how laws and regulations affect private sector development for agribusinesses, including producer organizations and other agricultural entrepreneurs. Globally comparable data and scored indicators encourage regulations that ensure safety and quality of agricultural inputs, goods and services but are not too costly or burdensome. The goal is to facilitate the operation of agribusinesses and allow them to thrive in a socially and environmentally responsible way, enabling them to provide essential agricultural inputs and services to farmers that could increase their productivity and profits. Regional, income-group and country-specific trends and data observations are presented for 62 countries and across twelve topics: seed, fertilizer, machinery, finance, markets, transport, water, ICT, land, livestock, environmental sustainability and gender. Data are current as of June 30, 2016.

The COVID-19 pandemic accelerated the adoption of new forms of working and new working arrangements largely enabled by technology. The Future of Work is a projection of how work, working, workers and the workplace will evolve in the years ahead from the perspective of different actors in society, influenced by technological, socio-economic, political, and demographic changes. This open access Pivot is a timely exploration of some of the challenges and prospects for the future of work from two main perspectives: how work is changing and how to prepare for work in the future. An evidence-based assessment of these topics offers some critical perspectives that challenge old assumptions and opens up emerging trends and possibilities for work in the future. As part of the Palgrave Studies in Digital Business & Enabling Technologies series, this book is an essential resource for academics of Business, Human Resource Management, Organisational Psychology and Industrial Relations, as well as practitioners and policy makers

PurposeThe purpose of this research is to explore the ways of integrating situational awareness into business process management for the purpose of realising hyper automated business processes. Such business processes will help improve their customer experiences, enhance the reliability of service delivery and lower the operational cost for a more competitive and sustainable business.Design/methodology/approachOntology has been deployed to establish the context modelling method, and the event handling mechanisms are developed on the basis of event calculus. An approach on performance of the proposed approach has been evaluation by checking the cost savings from the simulation of a large number of business processes.FindingsIn this research, the authors have formalised the context presentation for a business process with a focus on rules and entities to support context perception; proposed a system architecture to illustrate the structure and constitution of a supporting system for intelligent and situation aware business process management; developed real-time event elicitation and interpretation mechanisms to operationalise the perception of contextual dynamics and real-time responses; and evaluated the applicability of the proposed approaches and the performance improvement to business processes.Originality/valueThis paper presents a framework covering process context modelling, system architecture and real-time event handling mechanisms to support situational awareness of business processes. The reported research is based on our previous work on radio frequency identification-enabled applications and context-aware business process management with substantial extension to process context modelling and process simulation.

application; blueprints; self-management; self-organisation; resource management; supply chain; big data; PaaS; Saas; HPCaaS

"A practical guide to leveraging your data to spur innovation and growth. Your business generates reams of data, but what do you do with it? Reporting is only the beginning. Your data holds the key to innovation and growth - you just need the proper analytics. In Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics, author Evan Stubbs explores the potential gold hiding in your un-mined data. As Chief Analytics Officer for SAS Australia/New Zealand, Stubbs brings an industry insider's perspective to guide you through pattern recognition, analysis, and implementation. Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics details a groundbreaking approach to ensuring your company's upward trajectory. Use this guide to leverage your customer information, financial reports, performance metrics, and more to build a rock-solid foundation for future growth. Build an effective analytics team, and empower them with the right tools Learn how big data drives both evolutionary and revolutionary innovation, and who should be responsible Identify data collection and analysis opportunities and implement action plans Design the platform that suits your company's current and future needs Quantify performance with statistics, programming, and research for a more complete picture of operations Effective management means combining data, people, and analytics to create a synergistic force for innovation and growth. If you want your company to move forward with confidence, Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics can show you how to use what you already have and acquire what you need to succeed"--

The collection and long-term retention of excessive data enables organisations to process data for insights in non-primary processes. The discovery of insights is promoted to be useful both for organisations and the customers. However, long-term possession of data on one hand risks the privacy of data belonging beings in cases of data breaches and on the other hand results in the customers distrust. General Data Protection Regulation (GDPR) abstractly defined the data processing boundaries of the personal data of European Union's citizens. The processing principles of GDPR, in line with the spirit of privacy by design and default, provide directions on the collection, storage, and processing of personal data. Concomitantly, the data subject rights provides customers with necessary control over their personal data stationed at the data controller's premises. The accountability principle of GDPR requires compliance in place and also the ability to demonstrate it. In this work, we are providing three solutions to enable GDPR compliance in business processes. First, we are proposing intra-process data degradation, a solution for continuous data minimisation during the course of business processes. The proposed approach results in reduced data maintenance and breach losses. Second, we adapt process mining techniques for ascertaining compliance of business process execution to data subject rights. Finally, we present a scheme to utilise differential privacy technique to enable GDPR-compliant business process discovery. Additionally, we offer links to two effective tools that demonstrate our first and second contributions.

Enabling the Business of Agriculture 2016 provides a tool for policy makers to identify and analyze legal barriers for the business of agriculture and to quantify transaction costs of dealing with government regulations. Building on an earlier progress report published in November 2014, this volume presents the main results for 40 countries, for the first time using indicator scores to showcase good practices among countries in different stages of agricultural development. It also presents interesting results on the relationship between efficiency and quality of regulations, discriminatory practices in the laws, and whether regulatory information is accessible. Regional, income-group, and country-specific trends and data observations are presented on six topics: seed, fertilizer, machinery, finance, markets, and transport. The report also discusses the continued development of several topics that will be added in future reports: information and communication technology, land, water, livestock, gender, and environmental sustainability.

The IoT-as-a-Service (IoTaaS) business model has already been identified by some people from both industry and academia, but has not been formally defined. IoTaaS offers IoT devices on demand, with considerable cost savings and resource optimization. In addition, it enables different applications to reuse the existing devices. However, this business model is associated with different technological challenges that need to be addressed, one of which is the identity problem. Focusing on this, self-sovereign identity (SSI) schemes have proven to provide better privacy and scalability than traditional identity paradigms, which is especially important in the IoT owing to its characteristics. In this paper, we formally analyze an IoTaaS business model, identifying and detailing its main technological challenges. In addition, we tackle the identity problem of this business model and propose an SSI-based identity management system, which is compliant with the existing standards from the W3C, and include a performance evaluation. ; This work was supported in part by the Basque Country Government through the Collaborative Research Grants Program in Strategic Areas (ELKARTEK) Program by the Project TRUSTIND under Grant KK-2020/00054 and in part by the Spanish Government-Ministry of Science and Innovation through the Project AI4ES-2021 under Grant CER-20211030 and through the Project SICRAC under Grant PID2020-114495RB-I00