The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research suggests the need to compare and contrast different types of SEM techniques so that research designs can be appropriately selected. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squares-based SEM. Finally, the article discusses linear regression models and offers guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

Starting in September of 1997, David Gefen will be an assistant professor at the Drexel

and Knowledge Transfer, the special editor and two anonymous referees. The author would also like to acknowledge Himanshu Sheth’s help with statistical analysis. Financial support was graciously provided by the Reginald Jones Center and by the Hunstman Center at the Wharton School of the University of Pennsylvania. Errors and omissions are solely the author’s responsibility. 1 THE PROCESS OF KNOWLEDGE TRANSFER: A DIACHRONIC ANALYSIS OF STICKINESS Even though intra-firm transfers of knowledge are often laborious, time consuming and fraught with difficulty, extant conceptions treat them essentially as a costless and instantaneous exploit. When at all acknowledged, difficulty is an anomaly in the way transfers are modeled rather than a characteristic feature of the transfer itself. One first step towards incorporating difficulty in the analysis of knowledge transfer is to recognize that a transfer is not an act, as typically modeled, but a process. This paper offers a process model of knowledge transfer. The model identifies stages of transfer and factors that are expected to correlate with difficulty at different stages of the transfer. The general expectation is that factors that affect the opportunity

Price Premiums and Buyer Behavior Despite the wide use of reputational mechanisms such as eBay’s Feedback Forum to promote trust, empirical evidence has shown conflicting results on whether online feedback mechanisms really induce trust and lead to higher auction prices. This study examines the extent to which trust can be induced by proper feedback mechanisms in electronic markets, and how some risk factors play a role in trust formation. Drawing from economic, sociological, and marketing theories and using data from both an online experiment and an online auction market, we demonstrate that appropriate feedback mechanisms can induce calculus-based credibility trust without repeated interactions between two transacting parties. Trust can mitigate information asymmetry by reducing transaction-specific risks, therefore generating price premiums for reputable sellers. In addition, the research also examines the role that trust plays in mitigating the risks in transactions that involve very expensive products or experience products.

What explains differences in firms' abilities to acquire competitive capabilities? In this paper we propose that embeddedness, in terms of firms' network of bridging ties and linkages to regional institutions, are important sources of variation in firms' acquisition of competitive capabilities. We argue that firm networks rich in bridging ties and firms' participation in regional institutions are critical vehicles for accessing new information, ideas, and opportunities leading to the acquisition of competitive capabilities in geographical clusters. Hypotheses are tested on a stratified random sample of 227 job shop manufacturers located in several regions of the US Midwest using data gathered from a mailed questionnaire. Results from structural equation modeling broadly support the embeddedness hypotheses and suggest a number of novel insights about the link between firms' networks and competitive capabilities.

Are Americans more individualistic and less collectivistic than members of other groups? The authors summarize plausible psychological implications of individualism–collectivism (IND-COL), metaanalyze cross-national and within-United States IND-COL differences, and review evidence for effects of IND-COL on self-concept, well-being, cognition, and relationality. European Americans were found to be both more individualistic—valuing personal independence more—and less collectivistic—feeling duty to in-groups less—than others. However, European Americans were not more individualistic than African Americans, or Latinos, and not less collectivistic than Japanese or Koreans. Among Asians, only Chinese showed large effects, being both less individualistic and more collectivistic. Moderate IND-COL effects were found on self-concept and relationality, and large effects were found on attribution and cognitive style. To contemporary Americans, being an individualist is not only a good thing; it is a quintessentially American thing. However, the term individualism itself appears to have its roots outside of the North American continent, namely in the French Revolution. It appears that individualism was first used to describe the negative

The SPICE project aims to deliver an international standard for software process assessment by the end of 1996. As part of this project there is an empirical trials phase whose purpose is to ascertain the effectiveness of the prospective SPICE standard. Two of the objectives of the trials phase are: (a) to determine the extent to which SPICEconformant assessments are repeatable (i.e., reliability), and (b) to determine the extent to which SPICE-conformant assessments are really measuring best software process practices (i.e., validity). This paper introduces the theoretical foundations for evaluating the reliability and validity of measurement, suggests some empirical research methods for investigating them in SPICE, and discusses the constraints and limitations of these methods within the context of the SPICE project.

A review of the literature suggests that few studies use formative indicator measurement models, even though they should. Therefore, the purpose of this research is to (a) discuss the distinction between formative and reflective measurement models, (b) develop a set of conceptual criteria that can be used to determine whether a construct should be modeled as having formative or reflective indicators, (c) review the marketing literature to obtain an estimate of the extent of measurement model misspecification in the field, (d) estimate the extent to which measurement model misspecification biases estimates of the relationships between constructs using a Monte Carlo simulation, and (e) provide recommendations for modeling formative indicator constructs. It has been more than two decades since Churchill (1979), Bagozzi (1980), Peter (1981), and Anderson and Gerbing (1982), among others, criticized the field of marketing for failing to pay enough attention to construct validity and associated measurement issues. A good example of this concern

AbstractÐIn this paper, an empirical study that links software process consistency with product defects is reported. Various measurement issues such as validity, reliability, and other challenges in measuring process consistency at the project level are discussed. A measurement scale for software process consistency is introduced. An empirical study that uses this scale to measure consistency in achieving the CMM goal questions in various key process areas (KPAs) in 45 projects at a leading software vendor is reported. The results of this analysis indicate that consistent adoption of practices specified in the CMM is associated with a lower number of defects. Even a relatively modest improvement in the consistency of implementing these practices is associated with a significant reduction in field defects. Index TermsÐSoftware process consistency, software process measurement, CMM, software defects, empirical model. 1

Current methods to represent system or task usability in a single metric do not include all the ANSI and ISO defined usability aspects: effectiveness, efficiency & satisfaction. We propose a method to simplify all the ANSI and ISO aspects of usability into a single, standardized and summated usability metric (SUM). In four data sets, totaling 1860 task observations, we show that these aspects of usability are correlated and equally weighted and present a quantitative model for usability. Using standardization techniques from Six Sigma, we propose a scalable process for standardizing disparate usability metrics and show how Principal Components Analysis can be used to establish appropriate weighting for a summated model. SUM provides one continuous variable for summative usability evaluations that can be used in regression analysis, hypothesis testing and usability reporting. ACM Classification