Basics of qualitative research: Grounded theory procedures and techniques

The ability to detect and accurately estimate the strength of interaction effects are critical issues that are fundamental to social science research in general and IS research in particular. Within the IS discipline, a significant percentage of research has been devoted to examining the conditions and contexts under which relationships may vary, often under the general umbrella of contingency theory (cf. McKeen et al. 1994, Weill and Olson 1989). In our survey of such studies, the majority failed to either detect or provide an estimate of the effect size. In cases where effect sizes are estimated, the numbers are generally small. These results have led some researchers to question both the usefulness of contingency theory and the need to detect interaction effects (e.g., Weill and Olson 1989). This paper addresses this issue by providing a new latent variable modeling approach that can give more accurate estimates of interaction effects by accounting for the measurement error that attenuates the estimated relationships. The capacity of this approach at recovering true effects in comparison to summated regression is demonstrated in a Monte Carlo study that creates a simulated data set in which the underlying true effects are known. Analysis of a second, empirical data set is included to demonstrate the technique's use within IS theory. In this second analysis, substantial direct and interaction effects of enjoyment on electronic-mail adoption are shown to exist.

/pdf/a-partial-least-squares-latent-variable-modeling-approach-20dk7tba26.pdf

A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic-Mail Emotion/Adoption Study

Knowledge-intensive firms are composed of multiple communities with specialized expertise, and are often characterized by lateral rather than hierarchical organizational forms. We argue that producing knowledge to create innovative products and processes in such firms requires the ability to make strong perspectives within a community, as well as the ability to take the perspective of another into account. We present models of language, communication and cognition that can assist in the design of electronic communication systems for perspective making and perspective taking. By appreciating how communication is both like a language game played in a local community and also like a transmission of messages through a conduit, and by appreciating how cognition includes a capacity to narrativize our experience as well as a capacity to process information, we identify some guidelines for designing electronic communication systems to support knowledge work. The communication systems we propose emphasize that narratives can help construct strong perspectives within a community of knowing, and that reflecting upon and representing that perspective can create boundary objects which allow for perspective taking between communities. We conclude by describing our vision of an idealized knowledge intensive firm with a strong culture of perspective making and perspective taking, and by identifying some elements of the electronic communication systems we would expect to see in such a firm.

Perspective Making and Perspective Taking in Communities of Knowing

Generalizability is a major concern to those who do, and use, research. Statistical, sampling-based generalizability is well known, but methodologists have long been aware of conceptions of generalizability beyond the statistical. The purpose of this essay is to clarify the concept of generalizability by critically examining its nature, illustrating its use and misuse, and presenting a framework for classifying its different forms. The framework organizes the different forms into four types, which are defined by the distinction between empirical and theoretical kinds of statements. On the one hand, the framework affirms the bounds within which statistical, sampling-based generalizability is legitimate. On the other hand, the framework indicates ways in which researchers in information systems and other fields may properly lay claim to generalizability, and thereby broader relevance, even when their inquiry falls outside the bounds of sampling-based research.

/pdf/generalizing-generalizability-in-information-systems-727w9tiafy.pdf

Generalizing Generalizability in Information Systems Research

Enterprise resource planning (ERP) systems have emerged as the core of successful information management and the enterprise backbone of organizations. The difficulties of ERP implementations have been widely cited in the literature but research on the critical factors for initial and ongoing ERP implementation success is rare and fragmented. Through a comprehensive review of the literature, 11 factors were found to be critical to ERP implementation success – ERP teamwork and composition; change management program and culture; top management support; business plan and vision; business process reengineering with minimum customization; project management; monitoring and evaluation of performance; effective communication; software development, testing and troubleshooting; project champion; appropriate business and IT legacy systems. The classification of these factors into the respective phases (chartering, project, shakedown, onward and upward) in Markus and Tanis’ ERP life cycle model is presented and the importance of each factor is discussed.

Critical factors for successful implementation of enterprise systems

IntroductionOrganizations are becoming increasingly serious about the notion of "data as an asset" as they face increasing pressure for reporting a "single version of the truth." In a 2006 survey of 359 North American organizations that had deployed business intelligence and analytic systems, a program for the governance of data was reported to be one of the five success "practices" for deriving business value from data assets. In light of the opportunities to leverage data assets as well ensure legislative compliance to mandates such as the Sarbanes-Oxley (SOX) Act and Basel II, data governance has also recently been given significant prominence in practitioners' conferences, such as TDWI (The Data Warehousing Institute) World Conference and DAMA (Data Management Association) International Symposium.The objective of this article is to provide an overall framework for data governance that can be used by researchers to focus on important data governance issues, and by practitioners to develop an effective data governance approach, strategy and design. Designing data governance requires stepping back from day-to-day decision making and focusing on identifying the fundamental decisions that need to be made and who should be making them. Based on Weill and Ross, we also differentiate between governance and management as follows:• Governance refers to what decisions must be made to ensure effective management and use of IT (decision domains) and who makes the decisions (locus of accountability for decision-making).• Management involves making and implementing decisions.For example, governance includes establishing who in the organization holds decision rights for determining standards for data quality. Management involves determining the actual metrics employed for data quality. Here, we focus on the former.Corporate governance has been defined as a set of relationships between a company's management, its board, its shareholders and other stakeholders that provide a structure for determining organizational objectives and monitoring performance, thereby ensuring that corporate objectives are attained. Considering the synergy between macroeconomic and structural policies, corporate governance is a key element in not only improving economic efficiency and growth, but also enhancing corporate confidence. A framework for linking corporate and IT governance (see Figure 1) has been proposed by Weill and Ross.Unlike these authors, however, we differentiate between IT assets and information assets: IT assets refers to technologies (computers, communication and databases) that help support the automation of well-defined tasks, while information assets (or data) are defined as facts having value or potential value that are documented. Note that in the context of this article, we do not differentiate between data and information.Next, we use the Weill and Ross framework for IT governance as a starting point for our own framework for data governance. We then propose a set of five data decision domains, why they are important, and guidelines for what governance is needed for each decision domain. By operationalizing the locus of accountability of decision making (the "who") for each decision domain, we create a data governance matrix, which can be used by practitioners to design their data governance. The insights presented here have been informed by field research, and address an area that is of growing interest to the information systems (IS) research and practice community.

Designing data governance

The prior IS literature points to the importance of organizational context for predicting a firm's IS governance solution. However, for the most part this literature assumes that firms adopt a uniform IS governance solution for all business units and that this solution can be predicted by context variables at the overall organization level. The purpose of this study is to increase our knowledge about why firms implement a hybrid IS governance solution in which a subset of IS functions that includes systems development is decentralized to some business units, but not to other business units, in the same enterprise. A theoretical framework of context variables at the business unit level is first developed. An embedded, single case study provides an initial test of eight propositions derived from the framework, as well as an opportunity for theory building. Data are collected utilizing both deductive and inductive methods from IS and non-IS executives of a divisionalized Fortune 500 firm in which a uniform decentralized solution for systems development in place for almost a decade has recently been replaced by a hybrid solution. The case study findings suggest that a configuration of four variables characterizes a business unit context conducive to decentralized systems development governance organic decision-making, high business unit autonomy, a differentiation competitive strategy, and an unstable industry environment. As predicted, however, the influence of these variables is likely to be overridden and a “deviant” solution adopted when deficiencies in IT capabilities are perceived and there is a culture that supports structural change at the business unit level. Additional interview and survey data collected from the key stakeholders are then analyzed in order to develop a richer understanding of the dimensions of the IT capabilities construct at the business unit level. The notion of absorptive capacity provides a theoretical argument for the emergent findings. Implications for researching today's increasingly complex IS governance forms are then drawn.

Examining the Emergence of Hybrid IS Governance Solutions: Evidence From a Single Case Site

This study contributes to the growing body of literature on the value of enterprise resource planning (ERP) investments at the firm level. Using an organization integration lens that takes into account investments in complementary resources as well as an options thinking logic about the value of an ERP platform, we argue that not all ERP purchases have the same potential impact at the firm level due to ERP project decisions made at the time of purchase. Based on a sample of 116 investment announcements in United Statesbased firms between 1997 and 2001, we find support for our hypotheses that ERP projects with greater functional scope (two or more value-chain modules) or greater physical scope (multiple sites) result in positive, higher shareholder returns. Furthermore, the highest increases in returns (3.29) are found for ERP purchases with greater functional scope and greater physical scope; negative returns are found for projects with lesser functional scope and lesser physical scope. These findings provide empirical support for prior theory about the organizational integration benefits of ERP systems, the contribution of complementary resource investments to the business value of IT investments, and the growth options associated with IT platform investments. The article concludes with implications of our firm-level findings for this first wave of enterprise systems.

https://www.jstor.org/stable/pdfplus/23015772.pdf

ERP Investments and the Market Value of Firms: Toward an Understanding of Influential ERP Project Variables

Highly complex enterprise software packages have become a standard way of competing in many industries. By the late 1990s, enterprise resource planning (ERP) systems had enabled Fortune 500 firms to present one face to their customers via integrated cross-functional business processes, centralized databases, and point-and-click access to real-time operational data across the business. Today, enterprise systems for supply chain management (SCM) and customer relationship management (CRM) are following in the steps of ERP, and, in many cases, providing a foundation for e-business. Supplier relationship management systems are on the horizon. Based on our ERP research, we have identified five factors for successful implementation: (1) top management is engaged in the project, not just involved; (2) project leaders are veterans, and team members are decision makers; (3) third parties fill gaps in expertise and transfer their knowledge; (4) change management goes hand-in-hand with project planning; (5) A satisficing mindset prevails. Furthermore, we found that a projects position on the maturity curve (early adopter, early majority, or late majority) can influence the implementation route. These five success factors and three maturity curve positions are illustrated in three anonymous cases. The result is lessons for managing the complexities of the next wave of enterprise systems.

Managing the Next Wave of Enterprise Systems: Leveraging Lessons from ERP

In the last few years, the way in which systems are provided in many manufacturing and service organizations has changed significantly: rather than developing and maintaining customized mainframe applications for single business clients, IS professionals are involved in the implementation of large-scale, cross-functionally integrated, packaged systems on client-server platforms. Enterprise resource planning (ERP) systems are on-line, interactive systems that can provide a “total” solution to an organization’s information systems needs by addressing a large proportion of business functions. They support a process-oriented view of the business as well as business processes standardized across the enterprise. Today, these packages are implemented on client/server architectures that are more flexible and scalable than mainframe systems. Five major vendors of ERP software have emerged, with SAP AG being the leader with more than a 30% market share.

https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1118&context=icis1999

Carol V. Brown

Papers

Designing data governance

Examining the Emergence of Hybrid IS Governance Solutions: Evidence From a Single Case Site

ERP Investments and the Market Value of Firms: Toward an Understanding of Influential ERP Project Variables

Managing the Next Wave of Enterprise Systems: Leveraging Lessons from ERP

ERP implementation approaches: toward a contingency framework