Search results

Considering the emergence of e-commerce platforms and their integration into marketing channels, this paper aims to investigate how artificial intelligence (AI) resources – both technological and human – possessed by e-commerce platforms can enhance their channel power by acquiring market-based assets (relational and intellectual).

Based on resource-based theory and resource orchestration theory, the authors developed a framework tested using survey data gathered from the sellers, which incorporated six key variables: the e-commerce platform’s AI technology resources and human resources, rational and intellectual market-based assets, intraplatform competition and channel power. The analyses are performed using the regression analysis technique.

The empirical findings indicate that both technological and human AI resources are crucial in building channel power. In addition, market-based assets serve as a mediator in this relationship, while intraplatform competition moderates the effect of intellectual market-based assets on channel power negatively.

This study contributes to the existing literature by exploring how e-commerce platforms’ AI resources affect their channel power. The results offer valuable guidance to managers and researchers on optimizing AI resources to improve channel power.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

This paper aims to provide a complete analysis framework and prediction method for the construction of the patent securitization (PS) basic asset pool.

This paper proposes an integrated classification method based on genetic algorithm and random forest algorithm. First, comprehensively consider the patent value evaluation model and SME credit evaluation model, determine 17 indicators to measure the patent value and SME credit; Secondly, establish the classification label of high-quality basic assets; Then, genetic algorithm and random forest model are used to predict and screen high-quality basic assets; Finally, the performance of the model is evaluated.

The machine learning model proposed in this study is mainly used to solve the screening problem of high-quality patents that constitute the underlying asset pool of PS. The empirical research shows that the integrated classification method based on genetic algorithm and random forest has good performance and prediction accuracy, and is superior to the single method that constitutes it.

The main contributions of the article are twofold: firstly, the machine learning model proposed in this article determines the standards for high-quality basic assets; Secondly, this article addresses the screening issue of basic assets in PS.

This study aims to investigate the extent of Shariah compliance in wakalah sukuk and Shariah non-compliant risk disclosure in the sukuk documents and to analyse the risk management techniques associated with the disclosed risks.

This study uses qualitative document analysis as both data collection and analysis methods. The document analysis acts as a data collection method for 23 wakalah sukuk documents selected from 32 issuances of wakalah sukuk from 2017 to 2021. These sukuk documents were selected based on their availability from relevant websites. Document analysis, both content analysis and thematic analysis, were used to analyse the data. Codes were grounded from that data through keywords search of Shariah noncompliant risk and its risk management. Besides these, interviews were also conducted with four active industry players, i.e. two legal advisors of wakalah sukuk, a wakalah sukuk trustee and a sukuk institutional issuer. These interview data were analysed based on categorical themes, on the aspects of the extent of Shariah compliance in sukuk, and the participant’s views on the risk management techniques associated with the risks or used in the sukuk documents.

Overall, the findings reveal three types of Shariah non-compliant risks disclosed in the sukuk documents and seven risk management techniques associated with them. However, the disclosure and the risk management techniques can be considered minimal in contrast to the extent of Shariah compliance in a sukuk, i.e. Shariah compliance at the pre-issuance stage, ongoing stage and post-issuance stage. On top of these, it was also found from the interviews that not all risk management techniques are workable to manage Shariah non-compliant risk in sukuk. As a result, these findings suggest rigorous reviews of the existing Shariah non-compliance risk (SNCR) disclosures and risk management techniques by the relevant parties.

Sukuk documents used in the study are limited to corporate wakalah sukuk issued in Malaysia. Out of 32 issuances from 2015 to 2021, only 23 documents are available in relevant website. Thus, Shariah non-compliant risk disclosure and its risk management techniques analysed in this study are only limited in those documents.

The findings of this study suggest rigorous reviews on the existing Shariah non-compliance disclosures and risk management techniques. Other than these, future research in relation to uncommon risk management clauses, i.e. assurance, Shariah waiver and transfer of risk, are needed.

The insights presented in the analysis are of importance to sukuk issuers and the sukuk due diligence working group in enhancing the sukuk Shariah compliance and Shariah non-compliant risks disclosure and towards sukuk investors, in capturing and assessing Shariah non-compliant risks in a sukuk and to assist them to make informed investment decisions. More importantly, this study has found few areas of future study in relation to SNCR disclosures and SNCR risk management techniques.

The paper tries to investigate the impact of applications of the resource-based view (RBV) theory in the management field to improve the firm’s profitability. Global firms are innovating and adopting new technology, paving the way to improve their performance.

We have adopted RBV in management practices such as marketing, strategy, finance, and human resources.

RBV has gained researchers' attention with the growing competitive world and new challenges to retaining customers and achieving their pre-defined targets. We attempt to identify the issues related to the usage of RBV in management.

Using RBV in management may help researchers create a competitive mindset and be prepared for uncertain challenges in the business world.

The current scenario is dominated by an urgent need for economic recovery caused by the global health emergency that has been at work since January 2020. Digital transformation plays a crucial role in bringing about this recovery. However, the failure rate of digital transformation projects over the last 10 years is very high. Considering the growing demand for digital transformation from businesses, the digital transformation failure rate, if unchanged, could lead to an exponential growth in technical debt. Technical debt is acquired when the digital transformation to be deployed at a business fails. The accumulation of technical debt will lead not only to economic stalemate but possibly also to yet another setback.

The developed set of methodologies form what has been termed the Digital Transformation Governance Engineering Process (DTGEP). This process can help any business wishing to undertake a digital transformation project to materialize their project in a sustainable, productive and competitive way.

DTGEP prevents the generation of technical debt because organizational knowledge is aligned with the technological solution that best suits the needs of each business in order to support its strategic or business objectives.

DTGEP has already been used to successfully discover the relationship between business features and the prospective digital transformation. However, it needs to be applied in case studies on many other businesses across the economy in order to gather more accurate information that could be clustered by sectors.

DTGEP was tested on a set of 25 projects, and this paper reports several interesting findings regarding its use, like the impact of the digital transformation on different parts of the business model canvas (BMC) and the intellectual capital of the organization developing the digital transformation, and how the status of the organization's intangible assets affects the decision-making process with respect to the prospective digital transformation.

Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.

Our result of this paper aims to indicate that the beta pricing formula could be applied in a long-term model setting as well.

In this paper, we show that the capital asset pricing model can be derived from a three-period general equilibrium model.

We show that our extended model yields a Pareto efficient outcome.

The capital asset pricing model (CAPM) model can be used for pricing long-lived assets.

Long-term modelling and sustainability can be modelled in our setting.

Our results were only known for two periods. The extension to 3 periods opens up a large scope of applicational possibilities in asset pricing, behavioural analysis and long-term efficiency.

Literature has pointed that conventional financial development theories have inconclusive role on motivating new businesses. New ventures often consider the conventional system that passes through risk and provides fixed-interest lending as a burden. Comparatively, Islamic finance contributes using participative and equitable substitute for startups and has a potential in promoting new businesses. This study aims to investigate the holistic financial development index quadratic effect on entrepreneurship and include the moderating role of Islamic financing at national level.

Islamic banks of 21 nations constitute the unbalanced panel data. Financial development and entrepreneurship indices were developed using factor analysis and panel median regression to estimate the nonlinear financial market development effects and Islamic financing moderation model.

The results indicated that low financial market development is entrepreneurship deterring because of interest burden effect, which could be eased with a proportional increase in the Islamic financing, which is participative. The moderating effect has led to the categorization of the sample countries into entrepreneurship promoting and entrepreneurship discouraging with respect to the current incidence of financial market development and Islamic financing, which can help policymakers in understanding the entrepreneurship promoting combination of financial development and Islamic financing.

Central banks and Shari’ah advisory councils can adopt Islamic financing transition in the national financial inclusion policy for new business facilitation.

This study is instrumental in exploring the assessment of introducing Islamic financing while developing the financial sector on multidimensional entrepreneurship.

The purpose of this study is to identify the possible efficiency gains in using tokenization for the execution of public expenditure on governmental investments.

Through design science research methodology, the exploratory research produced a tokenized prototype in the blockchain, through the Ernst and Young OpsChain traceability solution, allowing automated processes in the stages of public expense. A focus group composed of auditors from the public sector evaluated the possibility of improving the quality of information available in the audited entities, where the tokens created represent and register the actions of public agents in the blockchain Polygon.

The consensus of the experts in the focus group indicated that the use of tokenization could improve the quality of the information, since the possibility of recording the activities of public agents in the metadata of the tokens at each stage of the execution of the expenditure allows the audited entities the advantages of the information recorded on the blockchain, according to the following ranking: first the immutability of audited data, followed by reliability, transparency, accessibility and efficiency of data structures.

This research makes an empirical contribution to the real use of tokenization in blockchain technology to the public sector through a value chain in which tokens were created and moved between the wallets of public agents to represent, register and track the operations regarding public expense execution.