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Article
Publication date: 19 December 2023

Sunday Olarinre Oladokun and Manya Mainza Mooya

Challenges of property data in developing markets have been reported by several authors. However, a deep understanding of the actual nature of this phenomenon in developing…

Abstract

Purpose

Challenges of property data in developing markets have been reported by several authors. However, a deep understanding of the actual nature of this phenomenon in developing markets is largely lacking as in-depth studies into the actual nature of data challenge in such markets are scarce in literature. Specifically, the available literature lacks clarity about the actual nature of data challenges that developing markets pose to valuers and how this affects valuation practice. This study provides this understanding with focus on the Lagos property market.

Design/methodology/approach

This study utilises a qualitative research approach. A total of 24 valuers were selected using snowballing sampling technique, and in-depth semi-structured interviews were conducted. Data collected were analysed using thematic analysis with the aid of NVivo 12 software.

Findings

The study finds that the main data-related challenge in the Lagos property market is the lack of database of market property transactions and not the lack or absence of transaction data as it has been emphasised in previous studies. Other data-related challenges identified include weak property rights institution with attendant transaction costs, underhand dealings among professionals, undocumented charges, undisclosed information, scarcity of data relating to specialised assets and limited access to the subject property and required documents during valuation. Also, the study unbundles the factors responsible for these challenges and how they affect valuation practice.

Practical implications

The study has implication for practice in the sense that the deeper knowledge of data challenges could provide insight into strategy to tackle the challenges.

Originality/value

This study contributes to the body of knowledge by offering a fresh and in-depth perspective to the issue of data challenges in developing markets and how the peculiar nature of the real estate market affects the nature of data challenges. The qualitative approach adopted in this study allowed for a deep enquiry into the phenomenon and resulted into an extended insight into the peculiar nature of data challenges in a typical developing property market.

Details

Journal of Property Investment & Finance, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-578X

Keywords

Article
Publication date: 20 June 2022

Lokesh Singh, Rekh Ram Janghel and Satya Prakash Sahu

Automated skin lesion analysis plays a vital role in early detection. Having relatively small-sized imbalanced skin lesion datasets impedes learning and dominates research in…

Abstract

Purpose

Automated skin lesion analysis plays a vital role in early detection. Having relatively small-sized imbalanced skin lesion datasets impedes learning and dominates research in automated skin lesion analysis. The unavailability of adequate data poses difficulty in developing classification methods due to the skewed class distribution.

Design/methodology/approach

Boosting-based transfer learning (TL) paradigms like Transfer AdaBoost algorithm can compensate for such a lack of samples by taking advantage of auxiliary data. However, in such methods, beneficial source instances representing the target have a fast and stochastic weight convergence, which results in “weight-drift” that negates transfer. In this paper, a framework is designed utilizing the “Rare-Transfer” (RT), a boosting-based TL algorithm, that prevents “weight-drift” and simultaneously addresses absolute-rarity in skin lesion datasets. RT prevents the weights of source samples from quick convergence. It addresses absolute-rarity using an instance transfer approach incorporating the best-fit set of auxiliary examples, which improves balanced error minimization. It compensates for class unbalance and scarcity of training samples in absolute-rarity simultaneously for inducing balanced error optimization.

Findings

Promising results are obtained utilizing the RT compared with state-of-the-art techniques on absolute-rare skin lesion datasets with an accuracy of 92.5%. Wilcoxon signed-rank test examines significant differences amid the proposed RT algorithm and conventional algorithms used in the experiment.

Originality/value

Experimentation is performed on absolute-rare four skin lesion datasets, and the effectiveness of RT is assessed based on accuracy, sensitivity, specificity and area under curve. The performance is compared with an existing ensemble and boosting-based TL methods.

Details

Data Technologies and Applications, vol. 57 no. 1
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 1 July 2014

Martin Odening and Zhiwei Shen

– The purpose of this paper is to review some challenges of insuring weather risk in agriculture and to discuss potential remedies for these problems.

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Abstract

Purpose

The purpose of this paper is to review some challenges of insuring weather risk in agriculture and to discuss potential remedies for these problems.

Design/methodology/approach

The paper is developed as a narrative on weather insurance based largely on existing literature.

Findings

Weather risks show characteristics that often violate classical requirements for insurability. First, some weather risks, particularly slowly emerging weather perils like drought, are spatially correlated and cause systemic risks. Second, climatic change may increase the volatility of weather variables and lead to non-stationary loss distributions, which causes difficulties in actuarial ratemaking. Third, limited availability of yield and weather data hinders the estimation of reliable loss distributions.

Practical implications

Some of the approaches discussed in this review, such as time diversification, local test procedures and the augmentation of observational data by expert knowledge, can be useful for crop insurance companies to improve their risk management and product design.

Originality/value

This study provides background and development information regarding weather insurance and also presents statistical tools and actuarial methods that support the assessment of weather risks as well as the design of weather and yield insurance products.

Details

Agricultural Finance Review, vol. 74 no. 2
Type: Research Article
ISSN: 0002-1466

Keywords

Open Access
Article
Publication date: 2 August 2022

Maria Cristina Pietronudo, Fuli Zhou, Andrea Caporuscio, Giuseppe La Ragione and Marcello Risitano

This article aims to understand the role of intermediaries that manage innovation challenges in the healthcare scenario. More specifically, it explores the role of digital…

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Abstract

Purpose

This article aims to understand the role of intermediaries that manage innovation challenges in the healthcare scenario. More specifically, it explores the role of digital platforms in addressing data challenges and fostering data-driven innovation in the health sector.

Design/methodology/approach

For exploring the role of platforms, the authors propose a theoretical model based on the platform’s dynamic capabilities, assuming that, because of their set of capabilities, platforms may trigger innovation practices in actor interactions. To corroborate the theoretical framework, the authors present a detailed in-depth case study analysis of Apheris, an innovative data-driven digital platform operating in the healthcare scenario.

Findings

The paper finds that the innovative data-driven digital platform can be used to revolutionize established practices in the health sector (a) accelerating research and innovation; (b) overcoming challenges related to healthcare data. The case study demonstrates how data and intellectual property sharing can be privacy-compliant and enable new capabilities.

Originality/value

The paper attempts to fill the gap between the use of the data-driven digital platform and the critical innovation practices in the healthcare industry.

Details

European Journal of Innovation Management, vol. 25 no. 6
Type: Research Article
ISSN: 1460-1060

Keywords

Article
Publication date: 22 November 2019

Nikolai Tsvetkov and Alexander Chekanov

This paper aims to expand knowledge on strategy and business model transformation by exploring how the increased data availability can threaten the competitive positioning of data

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Abstract

Purpose

This paper aims to expand knowledge on strategy and business model transformation by exploring how the increased data availability can threaten the competitive positioning of data-based firms.

Design/methodology/approach

The study uses two longitudinal cases design. The data include a review of 270 business acquisitions performed by IBM and Yahoo! between 1995 and 2018 relying on publicly available documentation, corporate annual reports, shareholders presentations and press releases.

Findings

The study provides insights into how the availability of data can affect business models and the competitive advantage of data-based firms. Successful business model transformation in data-based firms appear to be contingent on dual-purpose mergers and acquisitions (M&As), oriented toward data and data-processing activities.

Research limitations/implications

Inductive case studies yield results that require quantitative validation. The insights on business model transformation and M&As from this study were obtained within the context of data-intensive firms.

Practical implications

When formulating a growth strategy through M&As, strategists need to consider whether the current state of their competitive positioning requires single purpose acquisitions (e.g. data or data-processing capabilities) or dual-purpose acquisitions.

Originality/value

As data becomes a commoditized asset, further research and guidance are needed to assess the impact of this phenomenon on data-based business models. This study fulfills an identified need to gain insights into the relationship between business model transformation and M&A activity.

Details

Journal of Business Strategy, vol. 42 no. 3
Type: Research Article
ISSN: 0275-6668

Keywords

Article
Publication date: 28 February 2022

Sulemana Bankuoru Egala and Eric Afful-Dadzie

This study uses the technology fit–viability theory to study the performance of one of the early pioneers of open government data (OGD) in Africa. The study aims to investigate…

Abstract

Purpose

This study uses the technology fit–viability theory to study the performance of one of the early pioneers of open government data (OGD) in Africa. The study aims to investigate the task and technology fit, as well as the economic, IT infrastructure and organisational viability as performance measures for the Ghana Open Government Data (GOGD) initiative.

Design/methodology/approach

The study adopted a qualitative approach by interviewing key actors within the GOGD ecosystem, namely, the OGD implementing body, data suppliers and data users. The results were compared with established OGD best practices and standards around the world.

Findings

The results suggest that Ghana’s OGD architecture appears far from meeting its fit and viability goals because of lacklustre performance attributed to the following factors: a complete lack of synergy among various stakeholder groups and actors in the GOGD ecosystem, a lack of sustainable financial support for the implementing body, a shortage of qualified staff for the GOGD project and partial neglect of GOGD as a consequence of the implementation of a new project called eTransform.

Research limitations/implications

This research is limited to Ghana’s OGD initiative. Perhaps, a comparative study on the performance of other OGD initiatives in Africa and other developed countries will present another view of how OGD initiatives are performing across the globe. Again, the number of interviewees in the study may not be sufficient to generalise the results.

Practical implications

The study guides developing economies on how to examine national and international legal frameworks that have consequences on the usage of OGD at the national and sub-national levels. Besides, the study results will help implementing agencies and by extension government to be wary of the consequences of neglecting relevant stakeholders in the implementation process. The study also emphasizes on the need for developing economies to have sustainable funding and technical support for OGD implementation.

Social implications

The study helps shape citizens’ understanding of what the government is doing pursuant to making data readily available for them. Because OGD spurs innovations, citizens’ continuous involvement is key in the process of realising government drive to be open and accountable to citizens through data.

Originality/value

This research is the first, to the best of the authors’ knowledge, to present a retrospective and prospective view of a country’s OGD implementation to ascertain the country’s fit and viability. More uniquely, this study will be the first, to the best of the authors’ knowledge, in assessing the performance of OGD setup in Africa.

Details

Transforming Government: People, Process and Policy, vol. 16 no. 3
Type: Research Article
ISSN: 1750-6166

Keywords

Book part
Publication date: 9 September 2020

Emily Ryo and Ian Peacock

In the current era of intensified immigration enforcement and heightened risks of deportation even for long-term lawful permanent residents, citizenship has taken on a new meaning…

Abstract

In the current era of intensified immigration enforcement and heightened risks of deportation even for long-term lawful permanent residents, citizenship has taken on a new meaning and greater importance. There is also growing evidence that citizenship denials in their various forms have become inextricably linked to immigration enforcement. Who is denied citizenship, why, and under what circumstances? This chapter begins to address these questions by developing a typology of citizenship denials and providing an empirical overview of each type of citizenship denial. Taken together, the typology of citizenship denials and the accompanying empirical overview illustrate the close connection between immigration enforcement and citizenship rights in the United States.

Article
Publication date: 14 June 2013

Javed Siddiqui

The paper seeks to respond to calls by Jones for more studies exploring the possibility of operationalising accounting for biodiversity.

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Abstract

Purpose

The paper seeks to respond to calls by Jones for more studies exploring the possibility of operationalising accounting for biodiversity.

Design/methodology/approach

Archival data are used to produce a natural inventory report for the Sundarbans, the world's largest mangrove forest declared as a World Heritage site by UNESCO in 2007.

Findings

The study extends prior research on biodiversity accounting by exploring the applicability of Jones' natural inventory model in the context of Bangladesh. The results indicate that application of Jones' natural inventory model is feasible in the context of developing countries such as Bangladesh. It is also recognised that the socio‐economic and political environment prevailing in developing economies may lead to the emergence of important stakeholder groups including local civil society bodies, international donor agencies and foreign governments. Biodiversity accounting may provide a legitimate basis for the government in allaying concerns regarding environmental stewardship and assist in negotiations with powerful stakeholder groups on important issues such as financial assistance after natural disasters and claims to the global climate change fund.

Originality/value

This is one of the early attempts to operationalise biodiversity accounting in the context of a developing economy.

Details

Accounting, Auditing & Accountability Journal, vol. 26 no. 5
Type: Research Article
ISSN: 0951-3574

Keywords

Article
Publication date: 17 August 2018

Santanu Mandal

The importance of big data analytics (BDA) on the development of supply chain (SC) resilience is not clearly understood. To address this, the purpose of this paper is to explore…

3773

Abstract

Purpose

The importance of big data analytics (BDA) on the development of supply chain (SC) resilience is not clearly understood. To address this, the purpose of this paper is to explore the impact of BDA management capabilities, namely, BDA planning, BDA investment decision making, BDA coordination and BDA control on SC resilience dimensions, namely, SC preparedness, SC alertness and SC agility.

Design/methodology/approach

The study relied on perceptual measures to test the proposed associations. Using extant measures, the scales for all the constructs were contextualized based on expert feedback. Using online survey, 249 complete responses were collected and were analyzed using partial least squares in SmartPLS 2.0.M3. The study targeted professionals with sufficient experience in analytics in different industry sectors for survey participation.

Findings

Results indicate BDA planning, BDA coordination and BDA control are critical enablers of SC preparedness, SC alertness and SC agility. BDA investment decision making did not have any prominent influence on any of the SC resilience dimensions.

Originality/value

The study is important as it addresses the contribution of BDA capabilities on the development of SC resilience, an important gap in the extant literature.

Details

Information Technology & People, vol. 32 no. 2
Type: Research Article
ISSN: 0959-3845

Keywords

Article
Publication date: 29 December 2022

Zhenmin Yuan, Yuan Chang, Yunfeng Chen, Yaowu Wang, Wei Huang and Chen Chen

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and…

Abstract

Purpose

Precast wall lifting during prefabricated building construction faces multiple non-lean problems, such as inaccurate lifting-time estimation, unreasonable resource allocation and improper process design. This study aims to identify the pathways for improving lifting performance to advance lean construction of prefabricated buildings.

Design/methodology/approach

This study developed a methodological framework that integrates the discrete event simulation method, the elimination, combination, rearrangement and simplification (ECRS) technique and intelligent optimization tool. Two schemes of precast wall lifting, namely, the enterprise's business as usual (BAU) and enterprise-leading (EL) schemes, were set to benchmark lifting performance. Furthermore, a best-practice (BP) scheme was modeled from the perspective of lifting activity ECRS and resource allocation for performance optimization.

Findings

A real project was selected to test the effect of the methodological framework. The results showed that compared with the EL scheme, the BP scheme reduced the total lifting time (TLT) by 6.3% and mitigated the TLT uncertainty (the gap between the maximum and minimum time values) by 20.6%. Under the BP scheme, increasing the resource inputs produces an insignificant effect in reducing TLT, i.e. increasing the number of component operators in the caulking subprocess from one to two only shortened the TLT by 3.6%, and no further time reduction was achieved as more component operators were added.

Originality/value

To solve non-lean problems associated with prefabricated building construction, this study provides a methodological framework that can separate a typical precast wall lifting process into fine-level activities. Besides, it also identifies the pathways (including the learning effect mitigation, labor and machinery resource adjustment and activities’ improvement) to reducing TLT and its uncertainty.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

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