Recently, there has been considerable interest in evaluating newer computer architectures such as the Web services architecture and the network computer architecture. In this work we investigate the decision models of expert and novice IS managers when evaluating computing architectures for use in an organization. This task is important because several consumer choice models in the literature indicate that the evaluation of alternative products is a critical phase that consumers undergo prior to forming an attitude toward the product. Previous work on evaluating the performance of experts vs. novices has focused either on the process differences between them, or on the performance outcome differences, with work in MIS focusing primarily on process differences. In this work, we utilize a methodology that examines both aspects, by constructing individual decision models for each expert and novice in the study. There is a growing consensus in the management literature that while experts may follow different processes, very often their performance does not differ significantly from novices in the business domain.
Caveats When increasing the Paid-Up Capital Requirement for Commercial Banks in Developing Countries: A Study of Nepalese Banks Ruman K C, Akhilesh Bajaj Abstract Purpose: The minimum paid-up capital or common stock requirement has been increased for commercial banks in several developing economies, to strengthening their banking systems. This has led to consolidations and an increase in the lending capacity of banks. The literature is not clear on how the significant expansion in the size of a bank through consolidation impacts the profitability of a bank. In this work, we investigate the case of Nepalese commercial banks where paid-up capital requirements for commercial banks increased four-fold. Specifically, we investigate if operating profitability was impacted by different factors before and after the mandated increase. Design/methodology/approach: We collected financial data on six different large Nepalese banks, over a 10-year period for each bank, from their public financial statements. A panel data analysis was conducted on this sample of 60 observations, over two separate time periods: the pre-mandate period from 2007-2014 and the post-period from 2015-2017. Panel data regression was performed using the PLM package on the R data analysis platform. Findings: We find that credit exposure of banks had a positive impact on operating profit both pre and post mandate. However, non-performing loans did not impact operating profit prior to the mandated increase, but had a significant negative impact after the increase in paid-up capital requirements. Research limitations/implications: The theoretical contribution of this work is an analysis of the effect of increasing minimum capital requirements rapidly and significantly on commercial banks in a developing economy. We find that the expected consolidation of banks and increase in number of loans leads to greater credit risk assumed by the banks, even if non-performing assets were not a factor earlier, as was the case in our sample. Practical Implications: Increases in capital adequacy requirements as a result of Basel 2 and 3 must be implemented gradually, so that lending strategies by bank management have time to adapt to the larger volume of loans, especially in economies where non-performing assets are already negatively affecting financial performance. Resources should also be provided to ensure that localized knowledge specific to lending practices is not lost in the bank consolidation that follows.Social Implications: Local lending practices are an important driver of operational excellence in developing economies. Mandated mergers can lead to a loss of organizational knowledge and create a greater distance between the institution and the local borrowers in the community. This leads to greater non-performing loans which can negatively impact the operating profit of the bank. Originality/value: To the authors‟ knowledge, this is the first study to use panel data analysis to analyze the impact of lending practices on operating profitability both pre and post a mandated increase in paid-up capital or common stock requirements for commercial banks in a developing economy. Our findings offer prescriptive guidelines for future implementations of this policy in other economies. Full Text: PDF DOI: 10.15640/jfbm.v7n2a2
The current form of information on the world wide web (WWW) is mainly in the form of unstructured information on scattered web sites. The usual method of accessing this information is using keyword-based or directory-based search engines. Recently, an increasing number of organizations, bodies and associations are adopting XML (extensible markup language) document type definitions (DTD) with a view towards putting structured information on the WWW. As information becomes more structured, we anticipate the spread of large XML repositories that will be accessible on the WWW. To help search these repositories, we present a novel search tool: XSAR (XML Based Search Agent For Information Retrieval), to access these repositories. We describe the architecture and functionality of XSAR, analyze its performance along four metrics and compare it to alternate existing search mechanisms. This work demonstrates the feasibility of agent based search mechanisms on large information repositories.
Conceptual models representing data and business processes bridge the gap between requirements specified by end-users and software systems specifications used to fulfill these requirements. More often than not, the entire systems development methodology is driven by a specific conceptual model used in a given situation. For example, a well-known database system development methodology uses the Entity-Relationship data model to capture end-user requirements and to drive the development of the ensuing database application.Several models have been proposed and some have been used as front-end inputs for automated tools to help in systems development. The question facing systems development managers is: which conceptual model to adopt? One important criterion for the effectiveness of a model is its completeness. The completeness of conceptual models has been widely accepted as an important attribute for efficient development of an effective system. Our survey of existing work on evaluating and comparing existing conceptual business process models indicates that almost no work has been done on empirically evaluating completeness of the models in real business situations. The primary contribution of this research is the development of a metric to measure the level of completeness of conceptual business process models (CBPMs). A case study demonstrates the use of this metric to evaluate the completeness of a CBPM - the Integrated Definition Standards Model.
For many companies, investment in information systems (IS) is one of the largest expenditures in the firm's capital budget. An important goal of ex ante investment evaluation of an information system is to reasonably determine the return on investment (ROI) of the proposed information system. However, past research has shown that business managers have significant concerns about the soundness of ex ante ROI evaluations of information systems. This relates to the fact that several benefits of an IS are intangible and nonfinancial. In addition, it has long been recognized that, unlike many other capital projects, IS projects exhibit significant contextual interaction. Further, different professionals such as accountants and Information Technology (IT) personnel often use different approaches to evaluate a potential information system. This study develops a framework and methodology that integrates and accommodates the different perspectives of IT personnel, accountants, and business managers. We propose a flexible ex ante framework and methodology that integrates systems analysis, accounting, and strategy (SAAS). The framework evaluates financial and nonfinancial factors and uses analyses that consider investment approaches used by both IT and accounting personnel. The framework is evaluated in two different organizations and recommendations are made for both future research in this area and for the applied use of the framework by professionals.
Traditional business models are increasingly being replaced by newer business models based on relationships enabled by information technologies. In this chapter, we survey and categorize many of these new business models enabled by electronic commerce (e-commerce). The main contribution of this chapter is the proposal and analysis of a new business model enabled by e-commerce: the On-Demand Delivery Services (ODDS) model. The ODDS model of e-commerce is one in which the physical products for sale are delivered directly to the customer without the use of a third-party logistics provider, such as a common carrier. For purpose of analysis, we sub-categorize the ODDS model into three submodels: The ODDS Model A applies to business-to-consumer (B2C) online sellers of physical goods who own or control their own delivery vehicles and may provide further services to extend the value proposition for the buyer. The online grocer is a typical example of businesses in this category. The ODDS Model B applies to business-to-business (B2B) sellers of physical goods, who also own a significant portion of their delivery fleet and deliver goods on demand to local distributors or business customers. Office supply eMerchants provide an example of this model. The ODDS Model C applies to businesses that typically provide virtually instantaneous delivery of third-party goods to consumers or businesses. Businesses in this category own or control their own delivery fleet and add value by delivering items within very short periods of time, usually one-hour delivery.
Conceptual models have been evaluated along the dimensions of modeling complexity (how easy is it to create schemas given requirements?) and readability (how easy is it to understand the requirements by reading the model schema?). In this work, we present COGEVAL, a propositional framework based on cognitive theories to evaluate conceptual models. We synthesize work from the cognitive literature to develop the framework and show how it can be used to explain earlier empirical results as well as existing theoretical frameworks. We illustrate how COGEVAL can be used as a theoretical basis to empirically test readability. Unlike much of the earlier empirical work on readability, our approach isolates the effect of a model-independent variable (degree of fragmentation) on readability. From a practical perspective, our findings will have implications for both creators of new models and practitioners who use currently available models to create schemas.Request access from your librarian to read this chapter's full text.
