The primary United Nations E-Government Index is a composite of three component indices: telecommunications infrastructure, human capital, and online e-government services, where the first two can be seen as enablers of the third. This study investigates the addition of a complementary component index for institutional efficacy, which is hypothesized to be another enabling factor. The institutional efficacy index is operationalized using existing measures gathered and made available by the World Bank. Statistical analysis shows that the institutional efficacy index is indeed a significant, additional predictor of online e-government services across nations. Following the presentation of basic results, qualitative analyses are undertaken to develop an assortment of generic national profiles. Preliminary analyses of changes over time are also presented using data from prior years, and directions for future research are outlined.

Synergy between technological infrastructure and institutional efficacy is hypothesized to be a key enabler of national e-governments and is empirically demonstrated using objective measures for these two factors. For the research models proposed, composite variables are constructed from secondary sources, data are analyzed using moderated multiple regression, and robustness is demonstrated with assorted post hoc analyses, including model validation via replication. Well over half the variance in e-government across countries is explained by the single TI synergy term using data reported in 2008 (n = 60, adjusted R-2 = 0.618) and in 2010 (n = 103, adjusted R-2 = 0.651; n = 120, adjusted R-2 = 0.694). This simple linear regression model offers a straightforward way to visualize the relative positions of countries with respect to technological-institutional synergy and the extent of national e-government. Using the model to identify atypical countries and country clusters for further study is highlighted.

XBRL—eXtensible Business Reporting Language—is a manifestation of XML that is gaining acceptance and adoption by governmental regulatory agencies throughout the world for investment and financial reporting. Current efforts are underway to expand the usefulness of XBRL as a source of business intelligence and a framework for ensuring transparency throughout the information value chain. This paper presents a brief history of XBRL and an explanation of its current impact on business reporting to make the argument for its inclusion as an emerging technology topic in ICT research and education.

An international association advancing the multidisciplinary study of informing systems. Founded in 1998, the Informing Science Institute (ISI) is a global community of academics shaping the future of informing science.

We report on a research model that was developed and tested to empirically investigate the associations of education quality, on-the-job training, the maturity of information and communications technology (ICT) use by individuals, businesses and governments, and gross domestic product (GDP) per capita across 122 countries. Overall, the findings indicate that education quality is positively associated with GDP per capita, while on-the-job training is not. Education quality is positively associated with ICT use by individuals and governments, but weakly with ICT use by business. On-the-job training, however, is positively associated with all three domains of ICT use. We then separately analyze countries with higher and lower levels of GDP per capita and find both similarities and differences. Healthy composite reliabilities and R2s are obtained in all analyses. The research model, its analysis, and discussion of the results are presented. © 2008 Wiley Periodicals, Inc.

The interplay between decision-making and decision-support tools has proven puzzling for many years. One of the most popular decision-support tools, what-if analysis, is no exception. Decades of empirical studies have found positive, negative, and null effects. In this paper, we contrast the marginal-analysis decision-making strategy enabled by what-if with the anchoring and adjustment decision-making strategies prevalent among unaided decision makers. By using an aggregate production planning decision task, we develop a Monte Carlo simulation to model 1000 independent what-if decision-making episodes across a myriad of conditions. Results mirror and explain seemingly contradictory findings across multiple prior experiments. Thus, this paper formalizes a simulation approach that expands the scope of previous findings regarding unaided versus what-if analysis aided decision making and suggests that relative performance is quite sensitive to task conditions. In this light, then, performance effect differences in past research are to be expected. While our analysis involves a single task context, the larger and more important point is that, even within a single task context, performance differences between unaided and aided decision making are emergent.

This paper presents a fundamental theoretical model and realises new factor operationalisations for the model in order to explore the effects of three explanatory variables – technological readiness, institutional readiness and fiscal readiness – on the extent of online government services availability across countries. Significant effects are found in a path model with direct effects of t-readiness and i-readiness on e-government, and indirect effects of f-readiness on e-government mediated through t-readiness. Results are discussed, practical implications are drawn and future research directions are offered.

We hypothesize that four key national factors of e-readiness are associated with e-business and e-government development: national economic prosperity, technological innovativeness, institutional maturity, and Internet service provider competition. Using hierarchical regression with cross-sectional data on 122 countries, we show that these hypothesized factors are independently associated with nations' reported developmental success in the areas of e-government and e-business. These results are obtained using data for 2006 and are replicated using data for 2007. Between-groups analysis using regression provides evidence of the model's applicability to both developed and developing nations, where the four factors can serve as parsimonious indicators for e-readiness and as key areas for public policy. We then discuss implications and limitations of the present work. We conclude by highlighting the current outlook for progress in developing nations along the four dimensions investigated and suggest a targeted approach for public policy.

While e-business and e-government are becoming drivers for the socioeconomic modernization of nations, much remains to be learned about the economic, political, and infrastructural factors associated with nations' e-business and e-government activity. In recent years, numerous e-readiness frameworks - derived in large part from theory in developmental and institutional socioeconomics - have been proffered to help guide nations in these modernization efforts. The present study derives a research model based upon common variables across e-readiness frameworks as well as related prior research to investigate associations between hypothesized key national factors and reported levels of e-business and e-government activity. Six potentially key factors are identified, cascading from general national characteristics to internet-specific characteristics: general economic prosperity, technological innovativeness, and tertiary education; internet service provider competition, law, and penetration. Data made available by the World Bank, the International Telecommunications Union, UNESCO, and the World Economic Forum are used to investigate the hypothesized associations across ninety-two countries. PLS is used to analyze the models and shows that the proposed models explain substantial variance in reported e-business and e-government levels. Moreover, intriguing similarities and differences are found.

Decision Sciences Journal of Innovative EducationVolume 6, Issue 2 p. 247-250 Engaging Students in Statistics* Jeffrey E. Kottemann, Corresponding Author Jeffrey E. Kottemann Franklin P. Perdue School of Business, Salisbury University, 1101 Camden Ave., Salisbury, MD 21801, e-mail: jekottemann@salisbury.edu, fxsalimian@salisbury.eduCorresponding author.Search for more papers by this authorFatollah Salimian, Fatollah Salimian Franklin P. Perdue School of Business, Salisbury University, 1101 Camden Ave., Salisbury, MD 21801, e-mail: jekottemann@salisbury.edu, fxsalimian@salisbury.eduSearch for more papers by this author Jeffrey E. Kottemann, Corresponding Author Jeffrey E. Kottemann Franklin P. Perdue School of Business, Salisbury University, 1101 Camden Ave., Salisbury, MD 21801, e-mail: jekottemann@salisbury.edu, fxsalimian@salisbury.eduCorresponding author.Search for more papers by this authorFatollah Salimian, Fatollah Salimian Franklin P. Perdue School of Business, Salisbury University, 1101 Camden Ave., Salisbury, MD 21801, e-mail: jekottemann@salisbury.edu, fxsalimian@salisbury.eduSearch for more papers by this author First published: 21 July 2008 https://doi.org/10.1111/j.1540-4609.2008.00170.xCitations: 4 * We wish to thank the two anonymous reviewers for their valuable suggestions. Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume6, Issue2July 2008Pages 247-250 RelatedInformation

The purpose of this research is to develop and test a parsimonious research model of drivers of e-government. Specifically, we investigate individual and business internet use both as direct antecedents of the availability of online government services and as indirect factors mediated by government development of an information and communications technology (ICT) regulatory environment. Beginning with theoretical motivations provided by the New Institutional Economics, we develop and test our research model using data on 122 countries using 2006 data from the World Economic Forum's (WEF) Global Information Technology Report (GITR). Our findings indicate that business rather than individual internet usage has greater explanatory value as an antecedent to the availability of e-government services, and that the ICT legal environment mediates both relationships.

The purpose of this research is to develop and test a parsimonious theory of the drivers of global level e- government. Specifically, we compare individual and business usage of online government services both as direct antecedents and as indirect factors mediated by government development of an ICT regulatory environment. Using 2006 data from the World Economic Forum's (WEF) Government Information Technology Report (GITR), we develop and test our theory using data on 122 countries. Our findings indicate that business rather than individual usage of e-government services has greater explanatory value as an antecedent to the availability of those services, and that the ICT legal environment mediates both relationships.

Previous research indicates that decision makers are often reluctant to use potentially beneficial multi-criteria decision support systems (MCDSS). Prior research has not examined the specific impact of preference elicitation techniques on user acceptance of MCDSS. The present research begins to fill this gap by examining the effect on users’ MCDSS evaluations of two commonly used preference elicitation techniques, absolute measurement and pairwise comparisons, while holding constant all other aspects of the MCDSS and decision making task. Experimental results (N=153) indicate that users consider MCDSS with pairwise comparisons to be higher in decisional conflict, more effortful, less accurate, and overall less desirable to use than MCDSS with absolute measurements. Thus, any potential normative superiority of a preference elicitation technique must be balanced against its potentially adverse effects on user acceptance of the MCDSS within which it is employed. We present a research agenda for exploring the tradeoffs between objective validity and user acceptance in the design of decision analysis tools.

Research on the anchor-and-adjustment paradigm has concentrated on discrete, static judgment tasks rather than on decision making in a continuous, dynamic environment. In the experiment reported, we found anchoring-and-adjustment occurring in a continuous, dynamic environment. We also established that the anchoring-and-adjustment model differed from the classical models in both fit and economic performance.

A wide array of decision rules capable of significantly enhancing decision-making performance across a range of tasks has been available for many years. Unfortunately, decision makers have stubbornly resisted using them. The present research investigates factors that might encourage decision rule use. In a simulated production planning task, 157 subjects were offered the recommendations of a simple but powerful decision rule. In the base case, subjects underestimated the usefulness of the rule and were vastly outperformed by it. Two interventions aimed at increasing use of the decision rule were examined: (1) giving subjects explicit feedback comparing their performance with how well they would have done had they used the rule and (2) providing them an explicit description of the rule′s performance benefits. Feedback on performance relative to the rule substantially increased perceived usefulness of the rule, rule-usage behavior, and decision performance. Rule description had a less clear effect. There was no overall significant effect of rule description on perceived usefulness or performance, although there was a significant overall effect on two measures of rule-following behavior. This increased rule-following behavior translated into significant performance improvements for the groups not receiving feedback, but not for the groups receiving feedback. We conclude that showing decision makers the benefits of using a decision rule via explicit aggregate feedback comparing rule and non-rule performance is an effective and underutilized way to increase their perceptions of the rule′s usefulness, their use of the rule, and their decision-making performance. Explicitly describing the performance characteristics is a secondary significant determinant of rule usage, especially recommended in cases where it is not feasible to provide aggregate outcome feedback.

Recent empirical evidence indicates that computer-assisted what-if analysis does not predictably improve decision making. Why then is what-if analysis so widely used by decision makers? We argue that what-if analysis creates an "illusion of control" which leads decision makers to overestimate its effectiveness. A between-subjects experiment was conducted using a production planning task to test this conjecture. As hypothesized, subjects falsely believed that what-if analysis improved their decision making. In fact, what-if analysis users expressed inflated confidence beliefs yet post hoc analysis revealed that they actually performed significantly worse than nonusers in the trials immediately preceding belief measurement. In light of other research linking user acceptance of computer-based technologies to users′ performance perceptions, these results forewarn of sustained, but dysfunctional, use of what-if analysis.

Decision makers have expanding access to business information via computerized news retrieval systems. A greater understanding is needed about how this news retrieval information influences their performance and confidence. MBA students from an advanced finance course forecasted stock earnings using a computerized information system designed to simulate systems used in practice. Disguised actual company data were presented in three different treatments: baseline information, baseline plus redundant news information, and baseline plus nonredundant news information. The redundant information made subjects significantly more confident in their forecasts compared to the baseline case. The nonredundant information made subjects significantly more confident than both the baseline case and the redundant case. Forecast accuracy, however, was significantly diminished in both the redundant and nonredundant conditions compared to baseline. Thus, the additional news information, whether redundant or nonredundant, had the effect of degrading performance while increasing confidence. This indicates that decision makers may be poor judges of the usefulness of newly available information sources, and may be influenced by information that does not improve their performance under the false impression that it is helpful.

Decision support systems continue to be very popular in business, despite mixed research evidence as to their effectiveness. We hypothesize that what-if analysis, a prominent feature of most decision support systems, creates an “illusion of control” causing users to overestimate its effectiveness. Two experiments involving a production planning task are reported which examine decision makers' perceptions of the effectiveness of what-if analysis relative to the alternatives of unaided decision making, and quantitative decision rules. Experiment 1 found that almost all subjects believed what-if analysis was superior to unaided decision making, although using what-if analysis had no significant effect on performance. Experiment 2 found that decision makers were indifferent between what-if analysis and a quantitative decision rule which, if used, would have led to significant cost savings. Thus, what-if analysis did create an illusion of control: decision makers perceived performance differences where none existed, and did not detect large differences when they were present. In both experiments, decision makers exhibited difficulty realizing that their positive beliefs about what-if analysis were exaggerated. Such misjudgments could lead people to continue using what-if analysis even when it is not beneficial and to avoid potentially superior decision support technologies.

Model integration extends the scope of model management to include the dimension of manipulation as well. This invariably leads to comparisons with database theory. Model integration is viewed from four perspectives: Organizational, definitional, procedural, and implementational. Strategic modeling is discussed as the organizational motivation for model integration. Schema and process integration are examined as the logical and manipulation counterparts of model integration corresponding to data definition and manipulation, respectively. A model manipulation language based on structured modeling and communicating structured models is suggested which incorporates schema and process integration. The use of object-oriented concepts for designing and implementing integrated modeling environments is discussed. Model integration is projected as the springboard for building a theory of models equivalent in power to relational theory in the database community.