A Practical Approach for Improving B2C e-Commerce Services with a Trust Capability Maturity Model

2013 ◽  
Vol 5 (2) ◽  
pp. 22-36 ◽  
Author(s):  
Rath Jairak ◽  
Prasong Praneetpolgrang
Keyword(s):  
Assessment Tool ◽  
Capability Maturity Model ◽  
Success Factor ◽  
Maturity Model ◽  
Is Success ◽  
Trust Development ◽  
Capability Maturity ◽  
Development Framework ◽  
Quality Aspects ◽  
Antecedents And Consequences

Trust is mentioned as a key success factor for e-Commerce services. While many researchers have conducted comprehensive studies to investigate the antecedents and consequences of consumer trust, there has been little work on trust development framework. This paper therefore introduces the Trust Capability Maturity Model (TCMM) that proposes to identify trust and progressive improvement in Business-to-Customer (B2C) e-Commerce websites. Trust metrics in TCMM are mainly inherited from the quality aspects in the Delone and Mclean IS success model. TCMM is composed of three main components as follows: 1) internal structure, 2) maturity levels, and 3) assessment tool. After performing some minor modifications for TCMM, the practical evaluation of modified TCMM is demonstrated by two regional online bookstores. Based on both case studies, the evaluation results can be applied to determine the level of trust in other vendors. Following the TCMM roadmap, online vendors will be able to develop a trust-building strategy for creating value and maintaining trust in their websites.

The development of the data science capability maturity model: a survey-based research

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mert Onuralp Gökalp ◽  
Ebru Gökalp ◽  
Kerem Kayabay ◽  
Altan Koçyiğit ◽  
P. Erhan Eren
Keyword(s):  
Data Science ◽  
Gap Analysis ◽  
Process Capability ◽  
Capability Maturity Model ◽  
International Electrotechnical Commission ◽  
Maturity Model ◽  
Data Governance ◽  
Content Type ◽  
Capability Maturity ◽  
Development Framework

PurposeThe purpose of this paper is to investigate social and technical drivers of data science practices and develop a standard model for assisting organizations in their digital transformation by providing data science capability/maturity level assessment, deriving a gap analysis, and creating a comprehensive roadmap for improvement in a standardized way.Design/methodology/approachThis paper systematically reviews and synthesizes the existing literature-related to data science and 183 practitioners' considerations by employing a survey-based research method. By blending the findings of this research with a well-established process capability maturity model standard, International Organization for Standardization/International Electrotechnical Commission (ISO/IEC) 330xx, and following a methodological maturity development framework, a theoretically grounded model, entitled as the data science capability maturity model (DSCMM) was developed.FindingsIt was found that organizations seek a capability/maturity model standard to evaluate and improve their current data science capabilities. To close this research gap, the DSCMM is developed. It consists of six capability maturity levels and twenty-seven processes categorized under five process areas: organization, strategy management, data analytics, data governance and technology management.Originality/valueThis paper validates the need for a process capability maturity model for the data science domain and develops the DSCMM by integrating literature findings and practitioners' considerations into a well-accepted process capability maturity model standard to continuously assess and improve the maturity of data science capabilities of organizations.

Business Intelligence as a Service

2016 ◽  
pp. 2030-2048
Author(s):  
Marco Spruit ◽  
Tim de Boer
Keyword(s):  
Cloud Computing ◽  
Business Intelligence ◽  
Assessment Tool ◽  
Geographic Location ◽  
Capability Maturity Model ◽  
Maturity Model ◽  
High Expectations ◽  
Capability Maturity ◽  
Hype Cycle ◽  
The Creation

Demand for business intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is low, showing the importance of BI products for a modern organization. However, globalization changes the way organizations use BI, where geographic location and time independency is becoming more and more important. Gartner's hype-cycle on BI depicts the technology of BI as a Service as being almost on top of the hype cycle, indicating there are high expectations of this new technology. This research advances on existing literature on business intelligence and cloud computing from a development perspective by introducing the concept of business intelligence as a service (BIaaS). The most important deliverable is the BIaaS capability maturity model (CMM) that is introduced here. The BIaaS CMM explains the conceptual model of BIaaS by the creation of the first BIaaS capability model containing key capabilities of BIaaS. The capability model is further enhanced with maturity levels depicting the importance of each BIaaS capability, a maturity matrix suggesting a roadmap for BIaaS solution development, and a BIaaS assessment model introducing a tool for finding problem areas in existing BIaaS solutions. The developed BIaaS CMM ought to support (starting) BIaaS vendors to develop BIaaS solutions by providing an assessment tool for BIaaS solutions. The assessment outcome provides the current maturity of the BIaaS solution and also includes problem areas for solution improvement. The introduction of the CApability Maturity Positioning (CAMP) method for the development of a maturity matrix, which results in the BIaaS maturity model, is significantly different from conventional maturity modeling. To calculate the weight of each capability from the BIaaS capability model, a thorough product review of existing business intelligence and cloud computing products is performed. Analysis of the results and normalizing the outcome of that analysis together with the introduction of a calculation mapping, is input for the creation of the maturity matrix. The maturity matrix is the essential foundation for the developed business intelligence as a Service capability maturity model, which is the main deliverable of this research.

Business Intelligence as a Service

2014 ◽  
Vol 5 (4) ◽  
pp. 26-43 ◽  
Author(s):  
Marco Spruit ◽  
Tim de Boer
Keyword(s):  
Cloud Computing ◽  
Business Intelligence ◽  
Assessment Tool ◽  
Geographic Location ◽  
Assessment Model ◽  
Capability Maturity Model ◽  
Maturity Model ◽  
Capability Maturity ◽  
Hype Cycle ◽  
The Creation

Demand for business intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is low, showing the importance of BI products for a modern organization. However, globalization changes the way organizations use BI, where geographic location and time independency is becoming more and more important. Gartner's hype-cycle on BI depicts the technology of BI as a Service as being almost on top of the hype cycle, indicating there are high expectations of this new technology. This research advances on existing literature on business intelligence and cloud computing from a development perspective by introducing the concept of business intelligence as a service (BIaaS). The most important deliverable is the BIaaS capability maturity model (CMM) that is introduced here. The BIaaS CMM explains the conceptual model of BIaaS by the creation of the first BIaaS capability model containing key capabilities of BIaaS. The capability model is further enhanced with maturity levels depicting the importance of each BIaaS capability, a maturity matrix suggesting a roadmap for BIaaS solution development, and a BIaaS assessment model introducing a tool for finding problem areas in existing BIaaS solutions. The developed BIaaS CMM ought to support (starting) BIaaS vendors to develop BIaaS solutions by providing an assessment tool for BIaaS solutions. The assessment outcome provides the current maturity of the BIaaS solution and also includes problem areas for solution improvement. The introduction of the CApability Maturity Positioning (CAMP) method for the development of a maturity matrix, which results in the BIaaS maturity model, is significantly different from conventional maturity modeling. To calculate the weight of each capability from the BIaaS capability model, a thorough product review of existing business intelligence and cloud computing products is performed. Analysis of the results and normalizing the outcome of that analysis together with the introduction of a calculation mapping, is input for the creation of the maturity matrix. The maturity matrix is the essential foundation for the developed business intelligence as a Service capability maturity model, which is the main deliverable of this research.

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