Case study: Applied Digital Solutions I3 services platform

The purpose of this project is to analyze whether i3 Strategy of Applied Digital Solutions (ADS) was necessary to meet the fast-moving IT industry. i3 Services Strategy is an integrated corporate strategy to reengineer the organizational structure of ADS

Integrating Business Intelligence and Analytics in Managing Public Sector Performance: An Empirical Study

Business intelligence and analytics (BIA) is emerging as a critical area to boost organizational performance. Nowadays, data is not only important and valuable to the organization but recognized as necessary to spike the organization performance and success. As a result, many organizations spend a considerable amount of investment toward obtaining faster accurate information on a real-time basis. The previous study revealed that even though many organizations use business intelligence technologies for obtaining information, yet they still lack analytics implementation. Therefore, this study aims to discover the integrated implementation factors of business intelligence and analytics in managing organizational performance, particularly for organizations of the public sector. In achieving this, a depth literature review was carried out to identify the influential factors in the implementation of business intelligence, business analytics, and performance management. The subject matter experts in Business Intelligence (BI), Business Analytics (BA) and Organisational Performance Management (OPM) were invited to participate in this empirical study, which was conducted in Malaysia. The study was carried out through interviewing experts, in order to identify the essential factors for business intelligence and data analytics implementation. Twenty essential factors and sixty-four sub-factors were identified and analyzed to construct the integrated factors in BIA and OPM implementation. The result of the study revealed four integrated factors of the BIA and OPM implementation, such as skill, documentation, visualization, and work culture. Finance, data management, software, strategic planning, and decision-making are other factors integrated with BI, BA, and OPM respectively. Finally, this study illustrates the integrated factors in a visual form

A Roadmap to Reduce U.S. Food Waste by 20 Percent

The magnitude of the food waste problem is difficult to comprehend. The U.S. spends $218 billion a year -- 1.3% of GDP -- growing, processing, transporting, and disposing of food that is never eaten. The causes of food waste are diverse, ranging from crops that never get harvested, to food left on overfilled plates, to near-expired milk and stale bread. ReFED is a coalition of over 30 business, nonprofit, foundation, and government leaders committed to building a different future, where food waste prevention, recovery, and recycling are recognized as an untapped opportunity to create jobs, alleviate hunger, and protect the environment -- all while stimulating a new multi-billion dollar market opportunity. ReFED developed A Roadmap to Reduce U.S. Food Waste as a data-driven guide to collectively take action to reduce food waste at scale nationwide.This Roadmap report is a guide and a call to action for us to work together to solve this problem. Businesses can save money for themselves and their customers. Policymakers can unleash a new wave of local job creation. Foundations can take a major step in addressing environmental issues and hunger. And innovators across all sectors can launch new products, services, and business models. There will be no losers, only winners, as food finds its way to its highest and best use

Regionalizing telecommunications reform in West Africa

In recent years, there has been an increasing recognition that significant welfare gains could be realized through deep forms of regional integration which entail harmonization of legal, regulatory and institutional frameworks. Reforms that reduce cross-border transaction costs and improve the performance of “backbone” infrastructure services are arguably even more important for the creation of an open, unified regional economic space than trade policy reforms narrowly defined. This paper assesses the potential gains from regionalized telecommunications policy in West Africa. To this end, the paper: (i) discusses how regional cooperation can overcome national limits in technical expertise, enhance the capacity of nations credibly to commit to stable regulatory policy, and ultimately facilitate infrastructure investment in the region; (ii) identifies trade-distorting regulations that inhibit opportunities for regional trade and economic development, and so are good candidates for regional trade negotiations to reduce indirect trade barriers; and (iii) describes substantive elements of a harmonized regional regulatory policy that can deliver immediate performance benefits.E-Business,Environmental Economics&Policies,ICT Policy and Strategies,Transport Economics Policy&Planning,Emerging Markets

Data Autonomy

In recent years, “data privacy” has vaulted to the forefront of public attention. Scholars, policymakers, and the media have, nearly in unison, decried the lack of data privacy in the modern world. In response, they have put forth various proposals to remedy the situation, from the imposition of fiduciary obligations on technology platforms to the creation of rights to be forgotten for individuals. All these proposals, however, share one essential assumption: we must raise greater protective barriers around data. As a scholar of corporate finance and a scholar of corporate law, respectively, we find this assumption problematic. Data, after all, is simply information, and information can be used for beneficial purposes as well as harmful ones. Just as it can be used to discriminate and to embarrass, information can be used to empower and to improve. And while data privacy is often pitched at ending unauthorized data sharing, it all too often leads simply to the end of data sharing, period. This comes at a cost. Data silos can inhibit consumer choice, protect the positions of powerful incumbents, and reduce the efficiency of markets. The best example of these costs comes from the financial industry. For more than a century, banks and other financial institutions have built their information technology systems to keep financial records as private and nonshareable as possible. While security concerns can be a primary reason for such closed systems, banks also understand that financial data is an advantage that can protect them from market entry and competition. Banks can hold up consumers with unfavorable rates and inferior products as a result, and a set of market failures make it difficult for consumers to opt out. First, information asymmetries between consumers and financial institutions are large and difficult to resolve. Second, search and switch costs—the difficulty of finding out more information about the risks and benefits of financial products and of switching to a better financial service—are high in the financial industry. Finally, individuals struggle to take advantage of even simple financial strategies to save, borrow, and invest. Data sharing can help resolve these problems. The emergence of a new regulatory and technological framework called “open banking” raises the possibility of consumers being able to task trusted intermediaries with automatically analyzing their financial data, nudging them to achieve their goals, and switching them to better products, all in order to reduce the substantial inefficiencies in their financial lives. There is one problem, however. A combination of market failure and regulatory ambiguity has led to a situation in which data is limited, siloed, and inaccessible, thereby preventing individuals from using their data in efficient ways. Ultimately, this Article contends, resolving these problems will require us to replace the clarion call of “data privacy” with a new, more comprehensive concept, that of “data autonomy”—the ability of individuals to have control over their data. Data autonomy balances the need for data to be protected and secure with the need for it to be accessible and shareable. In this Article, we lay out a set of key principles that grant individuals a legal right to data autonomy, including a right of ownership over data, as well as obligations on institutions to safely share standardized and interoperable data with third parties that consumers so choose. Perhaps counterintuitively, the only way of expanding consumer welfare and protection today is by breaking down the barriers of data privacy

Data Autonomy

In recent years, “data privacy” has vaulted to the forefront of public attention. Scholars, policymakers, and the media have, nearly in unison, decried the lack of data privacy in the modern world. In response, they have put forth various proposals to remedy the situation, from the imposition of fiduciary obligations on technology platforms to the creation of rights to be forgotten for individuals. All these proposals, however, share one essential assumption: we must raise greater protective barriers around data. As a scholar of corporate finance and a scholar of corporate law, respectively, we find this assumption problematic. Data, after all, is simply information, and information can be used for beneficial purposes as well as harmful ones. Just as it can be used to discriminate and to embarrass, information can be used to empower and to improve. And while data privacy is often pitched at ending unauthorized data sharing, it all too often leads simply to the end of data sharing, period. This comes at a cost. Data silos can inhibit consumer choice, protect the positions of powerful incumbents, and reduce the efficiency of markets. The best example of these costs comes from the financial industry. For more than a century, banks and other financial institutions have built their information technology systems to keep financial records as private and nonshareable as possible. While security concerns can be a primary reason for such closed systems, banks also understand that financial data is an advantage that can protect them from market entry and competition. Banks can hold up consumers with unfavorable rates and inferior products as a result, and a set of market failures make it difficult for consumers to opt out. First, information asymmetries between consumers and financial institutions are large and difficult to resolve. Second, search and switch costs—the difficulty of finding out more information about the risks and benefits of financial products and of switching to a better financial service—are high in the financial industry. Finally, individuals struggle to take advantage of even simple financial strategies to save, borrow, and invest. Data sharing can help resolve these problems. The emergence of a new regulatory and technological framework called “open banking” raises the possibility of consumers being able to task trusted intermediaries with automatically analyzing their financial data, nudging them to achieve their goals, and switching them to better products, all in order to reduce the substantial inefficiencies in their financial lives. There is one problem, however. A combination of market failure and regulatory ambiguity has led to a situation in which data is limited, siloed, and inaccessible, thereby preventing individuals from using their data in efficient ways. Ultimately, this Article contends, resolving these problems will require us to replace the clarion call of “data privacy” with a new, more comprehensive concept, that of “data autonomy”—the ability of individuals to have control over their data. Data autonomy balances the need for data to be protected and secure with the need for it to be accessible and shareable. In this Article, we lay out a set of key principles that grant individuals a legal right to data autonomy, including a right of ownership over data, as well as obligations on institutions to safely share standardized and interoperable data with third parties that consumers so choose. Perhaps counterintuitively, the only way of expanding consumer welfare and protection today is by breaking down the barriers of data privacy

Of BI research : a tale of two communities

The Business intelligence (BI) literature is in flux, yet the knowledge about its varying theoretical roots remains elusive. This state of affairs draws from two different scientific communities (informatics and business) that have generated multiple research streams, which duplicate research, neglect each other’s contributions, and overlook important research gaps. In response, we structure the BI scientific landscape and map its evolution to offer scholars a clear view of where research on BI stands and the way forward. For this endeavor, we systematically review articles published in top-tier ABS journals and identify 120 articles covering 35 years of scientific research on BI. We then run a co-citation analysis of selected articles and their reference lists. This yields the structuring of BI scholarly community around six research clusters: Environmental Scanning (ES), Competitive Intelligence (CI), Market Intelligence (MI), Decision Support (DS), Analytics Technologies (AT), and Analytics Capabilities (AC). The Co-citation network exposed overlapping and divergent theoretical roots across the six clusters and permitted mapping the evolution of BI research following two pendulum swings. Our article contributes by 1) structuring the theoretical landscape of BI research, 2) deciphering the theoretical roots of BI literature, 3) mapping the evolution of BI scholarly community, and 4) suggesting an agenda for future research.© 2020 Emerald Publishing Limited. This manuscript version is made available under the Creative Commons Attribution–NonCommercial 4.0 International (CC BY–NC 4.0) license, https://creativecommons.org/licenses/by-nc/4.0/fi=vertaisarvioitu|en=peerReviewed

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse

Ecosystem synergies, change and orchestration

This thesis investigates ecosystem synergies, change, and orchestration. The research topics are motivated by my curiosity, a fragmented research landscape, theoretical gaps, and new phenomena that challenge extant theories. To address these motivators, I conduct literature reviews to organise existing studies and identify their limited assumptions in light of new phenomena. Empirically, I adopt a case study method with abductive reasoning for a longitudinal analysis of the Alibaba ecosystem from 1999 to 2020. My findings provide an integrated and updated conceptualisation of ecosystem synergies that comprises three distinctive but interrelated components: 1) stack and integrate generic resources for efficiency and optimisation, 2) empower generative changes for variety and evolvability, and 3) govern tensions for sustainable growth. Theoretically grounded and empirically refined, this new conceptualisation helps us better understand the unique synergies of ecosystems that differ from those of alternative collective organisations and explain the forces that drive voluntary participation for value co-creation. Regarding ecosystem change, I find a duality relationship between intentionality and emergence and develop a phasic model of ecosystem sustainable growth with internal and external drivers. This new understanding challenges and extends prior discussions on their dominant dualism view, focus on partial drivers, and taken-for-granted lifecycle model. I propose that ecosystem orchestration involves systematic coordination of technological, adoption, internal, and institutional activities and is driven by long-term visions and adjusted by re-visioning. My analysis reveals internal orchestration's important role (re-envisioning, piloting, and organisation architectural reconfiguring), the synergy and system principles in designing adoption activities, and the expanding arena of institutional activities. Finally, building on the above findings, I reconceptualise ecosystems and ecosystem sustainable growth to highlight multi-stakeholder value creation, inclusivity, long-term orientation and interpretative approach. The thesis ends with discussing the implications for practice, policy, and future research.Open Acces