In order to determine how data mining techniques (DMT) and their applications have developed, during the past decade, this paper reviews data mining techniques and their applications and development, through a survey of literature and the classification of articles, from 2000 to 2011. Keyword indices and article abstracts were used to identify 216 articles concerning DMT applications, from 159 academic journals (retrieved from five online databases), this paper surveys and classifies DMT, with respect to the following three areas: knowledge types, analysis types, and architecture types, together with their applications in different research and practical domains. A discussion deals with the direction of any future developments in DMT methodologies and applications: (1) DMT is finding increasing applications in expertise orientation and the development of applications for DMT is a problem-oriented domain. (2) It is suggested that different social science methodologies, such as psychology, cognitive science and human behavior might implement DMT, as an alternative to the methodologies already on offer. (3) The ability to continually change and acquire new understanding is a driving force for the application of DMT and this will allow many new future applications.

https://romisatriawahono.net/lecture/rm/survey/machine%20learning/Liao%20-%20Data%20mining%20techniques%20and%20applications%20A%20decade%20review%20from%202000%20to%202011%20-%202012.pdf

Review: Data mining techniques and applications - A decade review from 2000 to 2011

Evaluating E-learning systems success : an empirical study

https://isiarticles.com/bundles/Article/pre/pdf/1148.pdf

Risk management in ERP project introduction: Review of the literature

Much research has been devoted over the years to investigating and advancing the techniques and tools used by analysts when they model. As opposed to what academics, software providers and their resellers promote as should be happening, the aim of this research was to determine whether practitioners still embraced conceptual modeling seriously. In addition, what are the most popular techniques and tools used for conceptual modeling? What are the major purposes for which conceptual modeling is used? The study found that the top six most frequently used modeling techniques and methods were ER diagramming, data flow diagramming, systems flowcharting, workflow modeling, UML, and structured charts. Modeling technique use was found to decrease significantly from smaller to medium-sized organizations, but then to increase significantly in larger organizations (proxying for large, complex projects). Technique use was also found to significantly follow an inverted U-shaped curve, contrary to some prior explanations. Additionally, an important contribution of this study was the identification of the factors that uniquely influence the decision of analysts to continue to use modeling, viz., communication (using diagrams) to/from stakeholders, internal knowledge (lack of) of techniques, user expectations management, understanding models' integration into the business, and tool/software deficiencies. The highest ranked purposes for which modeling was undertaken were database design and management, business process documentation, business process improvement, and software development.

/pdf/how-do-practitioners-use-conceptual-modeling-in-practice-2wff0djta3.pdf

How do practitioners use conceptual modeling in practice

With the growing recognition of the customer's role in service creation and delivery, there is an increased impetus on building customer-centric organizations. Digital technologies play a key role in such organizations. Prior research studying digital business strategies has largely focused on building production-side competencies and there has been little focus on customer-side digital business strategies to leverage these technologies. We propose a theory to understand the effectiveness of a customer-side digital business strategy focused on localized dynamics--here, a firm's customer service units (CSUs). Specifically, we use a capabilities perspective to propose digital design as an antecedent to two customer service capabilities--namely, customer orientation capability and customer response capability--across a firm's CSUs. These two capabilities will help a firm to locally sense and respond to customer needs, respectively. Information quality from the digital design of the CSU is proposed as the antecedent to the two capabilities. Proposed capability-building dynamics are tested using data collected from multiple respondents across 170 branches of a large bank. Findings suggest that the impacts of information quality in capability-building are contingent on the local process characteristics. We offer implications for a firm's customer-side digital business strategy and present new areas for future examination of such strategies.

https://ftp.misq.org/skin/frontend/default/misq/pdf/appendices/2013/V37I2_Appendices/SI_DBS_SetiaVenkateshAppendices.pdf

Leveraging digital technologies: how information quality leads to localized capabilities and customer service performance

Increased organizational dependence on information systems drives management attention towards improving information systems' quality. A recent survey shows that ''Improve IT quality'' is one of the top concerns facing IT executives. As IT quality is a multidimensional measure, it is important to determine what aspects of IT quality are critical to organizations to help Chief Information Officers (CIOs) to devise effective IT quality improvement strategies. In this research, we model the relationship between information systems' (IS) quality and organizational impact. We hypothesize greater organizational impact in situations in which system quality, information quality and service quality are high. We also hypothesize a positive relationship between system quality and information quality. We test our hypotheses using survey data. Our structural equation model exhibits a good fit with the observed data. Our results show that IS service quality is the most influential variable in this model (followed by information quality and system quality), thus highlighting the importance of IS service quality for organizational performance. This paper contributes theoretically to IS success models through the system quality-to-information quality and IS quality-to-organizational impact links. Implications of our results for practice and research are discussed.

/pdf/organizational-impact-of-system-quality-information-quality-4tq5nzcxoa.pdf

Organizational impact of system quality, information quality, and service quality

Personality type analysis can help take the guesswork out of putting together a high-performance software project team.

Who should work with whom?: building effective software project teams

The impact of IT outsourcing on information systems success

Software quality is important for the success of any information systems (IS). In this research, we find the determinants of software quality. We used five attributes for software quality: system reliability, maintainability, ease of use, usefulness, and relevance. By surveying 112 IS project managers, we collected data about their perceptions on the software quality attributes and their determinants. We arrived at six factors through exploratory factor analysis. We determined the individual factors that impacted the software quality attributes; for example, reliability is associated with responsiveness of IS department; ease of use is influenced by the capabilities of users and attitude of management; and usefulness is impacted by capabilities of IS department and responsiveness of IS department. We show that organizational factors are more important than technical factors in impacting software quality in IS projects. We provide implications of our research to practice and to future research.

Determinants of software quality: A survey of information systems project managers

Evaluating and assessing the important distinctions between data processing capability and data currency.

Narasimhaiah Gorla

Papers

Organizational impact of system quality, information quality, and service quality

Who should work with whom?: building effective software project teams

The impact of IT outsourcing on information systems success

Determinants of software quality: A survey of information systems project managers

Features to consider in a data warehousing system