Consequences of interorganizational information systems: An empirical investigation of the effects of EDI use on interorganizational relationships in the retail industry

This dissertation examines the consequences of Electronic Data Interchange (EDI) use on interorganizational relations (IR) in the retail industry. EDI is a type of interorganizational information system that facilitates the exchange of business documents in structured, machine processable form. The research model links EDI use and three IR dimensions--structural, behavioral, and outcome. Based on relevant literature from organizational theory and marketing channels, fourteen hypotheses were proposed for the relationships among EDI use and the three IR dimensions.^ Data were collected through self-administered questionnaires from key informants in 97 retail companies (19% response rate). The hypotheses were tested using multiple regression analysis. The analysis supports the following hypothesis: (a) EDI use is positively related to information intensity and formalization, (b) formalization is positively related to cooperation, (c) information intensity is positively related to cooperation, (d) conflict is negatively related to performance and satisfaction, (e) cooperation is positively related to performance, and (f) performance is positively related to satisfaction. The results support the general premise of the model that the relationship between EDI use and satisfaction among channel members has to be viewed within an interorganizational context.^ Research on EDI is still in a nascent stage. By identifying and testing relevant interorganizational variables, this study offers insights for practitioners managing boundary-spanning activities in organizations using or planning to use EDI. Further, the thesis provides avenues for future research aimed at understanding the consequences of this interorganizational information technology. ^

The effects of climate on the growth and physiology of tropical rainforest trees

Tropical rainforests account for more than a third of global net primary production and contain more than half of the global forest carbon. Though these forests are a disproportionately important component of the global carbon cycle, the relationship between rainforest productivity and climate remains poorly understood. Understanding the link between current climate and rainforest tree stem diameter increment, a major constituent of forest productivity, will be crucial to efforts at modeling future climate and rainforest response to climate change. This work reports the physiological and stem growth responses to micrometeorological and phenological states of ten species of canopy trees in a Costa Rican wet tropical forest at sub-annual time intervals. I measured tree growth using band dendrometers and estimated leaf and reproductive phenological states monthly. Electronic data loggers recorded xylem sap flow (an indicator of photosynthetic rate) and weather at half-hour intervals. An analysis of xylem sap flow showed that physiological responses were independent of species, which allowed me to construct a general model of weather driven sap flow rates. This model predicted more than eighty percent of climate driven sap flow variation. Leaf phenology influenced growth in three of the ten species, with two of these species showing a link between leaf phenology and weather. A combination of rainfall, air temperature, and irradiance likely provided the cues that triggered leaf drop in Dipteryx panamensis and Lecythis ampla. Combining the results of the sap flow model, growth, and the climate measures showed tree growth was correlated to climate, though the majority of growth variation remained unexplained. Low variance in the environmental variables and growth rates likely contributed to the large amount of unexplained variation. A simple model that included previous growth increment and three meteorological variables explained from four to nearly fifty percent of the growth variation. Significant growth carryover existed in six of the ten species, and rainfall was positively correlated to growth in eight of the ten species. Minimum nighttime temperature was also correlated to higher growth rates in five of the species and irradiance in two species. These results indicate that tropical rainforest tree trunks could act as carbon sinks if future climate becomes wetter and slightly warmer. ^

Performance analysis of disk mirroring techniques

Unequaled improvements in processor and I/O speeds make many applications such as databases and operating systems to be increasingly I/O bound. Many schemes such as disk caching and disk mirroring have been proposed to address the problem. In this thesis we focus only on disk mirroring. In disk mirroring, a logical disk image is maintained on two physical disks allowing a single disk failure to be transparent to application programs. Although disk mirroring improves data availability and reliability, it has two major drawbacks. First, writes are expensive because both disks must be updated. Second, load balancing during failure mode operation is poor because all requests are serviced by the surviving disk. Distorted mirrors was proposed to address the write problem and interleaved declustering to address the load balancing problem. In this thesis we perform a comparative study of these two schemes under various operating modes. In addition we also study traditional mirroring to provide a common basis for comparison.

A novel lossless compression technique for text data

The focus of this thesis is placed on text data compression based on the fundamental coding scheme referred to as the American Standard Code for Information Interchange or ASCII. The research objective is the development of software algorithms that result in significant compression of text data. Past and current compression techniques have been thoroughly reviewed to ensure proper contrast between the compression results of the proposed technique with those of existing ones. The research problem is based on the need to achieve higher compression of text files in order to save valuable memory space and increase the transmission rate of these text files. It was deemed necessary that the compression algorithm to be developed would have to be effective even for small files and be able to contend with uncommon words as they are dynamically included in the dictionary once they are encountered. A critical design aspect of this compression technique is its compatibility to existing compression techniques. In other words, the developed algorithm can be used in conjunction with existing techniques to yield even higher compression ratios. This thesis demonstrates such capabilities and such outcomes, and the research objective of achieving higher compression ratio is attained.

The adoption of retail electronic commerce: An empirical investigation

The purpose of this study was to empirically investigate the adoption of retail electronic commerce (REC). REC is a business transaction which takes place over the Internet between a casual consumer and a firm. The consumer has no long-term relationship with the firm, orders a good or service, and pays with a credit card. To date, most REC applications have not been profitable. To build profitable REC applications a better understanding of the system's users is required. ^ The research model hypothesizes that the level of REC buying is dependent upon the Buying Characteristics of Internet Use and Search Experience plus the Channel Characteristics of Beliefs About Internet Vendors and Beliefs About Internet Security. The effect of these factors is modified by Time. Additional research questions ask about the different types of REC buyers, the differences between these groups, and how these groups evolved over time. ^ To answer these research questions I analyzed publicly available data collected over a three-year period by the Georgia Institute of Technology Graphics and Visualization Unit over the Internet. Findings indicate the model best predicts Number of Purchases in a future period, and that Buyer Characteristics are most important to this determination. Further, this model is evolving over Time making Buyer Characteristics predict Number of Purchases better in more recent survey administrations. Buyers clustered into five groups based on level of buying and move through various levels and buy increasing Number of Purchases over time. ^ This is the first large scale research project to investigate the evolution of REC. This implications are significant. Practitioners with casual consumer customers need to deploy a finely tuned REC strategy, understand their buyers, capitalize on the company reputation on the Internet, install an Internet-compatible infrastructure, and web-enable order-entry/inventory/fulliment/shipping applications. Researchers might wish to expand on the Buyer Characteristics of the model and/or explore alternative dependent variables. Further, alternative theories such as Population Ecology or Transaction Cost Economics might further illuminate this new I.S. research domain. ^

Electronic Database Support Systems for Strategic Planning Activities in the Hospitality Industry

An electronic database support system for strategic planning activities can be built by providing conceptual and system specific information. The design and development of this type of system center around the information needs of strategy planners. Data that supply information on the organization's internal and external environments must be originated, evaluated, collected, organized, managed, and analyzed. Strategy planners may use the resulting information to improve their decision making.

Hospitality Data Mining Myths

Electronic database handling of buisness information has gradually gained its popularity in the hospitality industry. This article provides an overview on the fundamental concepts of a hotel database and investigates the feasibility of incorporating computer-assisted data mining techniques into hospitality database applications. The author also exposes some potential myths associated with data mining in hospitaltiy database applications.

Strategic positioning of Taiwan in the outsourcing market: Evidence from information technology services and electronic manufacturing outsourcing to China

In outsourcing relationships with China, the Electronic Manufacturing (EM) and Information Technology Services (ITS) industry in Taiwan may possess such advantages as the continuing growth of its production value, complete manufacturing supply chain, low production cost and a large-scale Chinese market, and language and culture similarity compared to outsourcing to other countries. Nevertheless, the Council for Economic Planning and Development of Executive Yuan (CEPD) found that Taiwan's IT services outsourcing to China is subject to certain constraints and might not be as successful as the EM outsourcing (Aggarwal, 2003; CEPD, 2004a; CIER, 2003; Einhorn and Kriplani, 2003; Kumar and Zhu, 2006; Li and Gao, 2003; MIC, 2006). Some studies examined this issue, but failed to (1) provide statistical evidence about lower prevalence rates of IT services outsourcing, and (2) clearly explain the lower prevalence rates of IT services outsourcing by identifying similarities and differences between both types of outsourcing contexts. This research seeks to fill that gap and possibly provide potential strategic guidelines to ITS firms in Taiwan. This study adopts Transaction Cost Economics (TCE) as the theoretical basis. The basic premise is that different types of outsourcing activities may incur differing transaction costs and realize varying degrees of outsourcing success due to differential attributes of the transactions in the outsourcing process. Using primary data gathered from questionnaire surveys of ninety two firms, the results from exploratory analysis and binary logistic regression indicated that (1) when outsourcing to China, Taiwanese firms' ITS outsourcing tends to have higher level of asset specificity, uncertainty and technical skills relative to EM outsourcing, and these features indirectly reduce firms' outsourcing prevalence rates via their direct positive impacts on transaction costs; (2) Taiwanese firms' ITS outsourcing tends to have lower level of transaction structurability relative to EM outsourcing, and this feature indirectly increases firms' outsourcing prevalence rates via its direct negative impacts on transaction costs; (3) frequency does influence firms' transaction costs in ITS outsourcing positively, but does not bring impacts into their outsourcing prevalence rates, (4) relatedness does influence firms' transaction costs positively and prevalence rates negatively in ITS outsourcing, but its impacts on the prevalence rates are not caused by the mediation effects of transaction costs, and (5) firm size of outsourcing provider does not affect firms' transaction costs, but does affect their outsourcing prevalence rates in ITS outsourcing directly and positively. Using primary data gathered from face-to-face interviews of executives from seven firms, the results from inductive analysis indicated that (1) IT services outsourcing has lower prevalence rates than EM outsourcing, and (2) this result is mainly attributed to Taiwan's core competence in manufacturing and management and higher overall transaction costs of IT services outsourcing. Specifically, there is not much difference between both types of outsourcing context in the transaction characteristics of reputation and most aspects of overall comparison. Although there are some differences in the feature of firm size of the outsourcing provider, the difference doesn't cause apparent impacts on firms' overall transaction costs. The medium or above medium difference in the transaction characteristics of asset specificity, uncertainty, frequency, technical skills, transaction structurability, and relatedness has caused higher overall transaction costs for IT services outsourcing. This higher cost might cause lower prevalence rates for ITS outsourcing relative to EM outsourcing. Overall, the interview results are consistent with the statistical analyses and provide support to my expectation that in outsourcing to China, Taiwan's electronic manufacturing firms do have lower prevalence rates of IT services outsourcing relative to EM outsourcing due to higher transaction costs caused by certain attributes. To solve this problem, firms' management should aim at identifying alternative strategies and strive to reduce their overall transaction costs of IT services outsourcing by initiating appropriate strategies which fit their environment and needs.

A Comparative Study of Concurrent Acoustic and Diver Survey Data, and Fish Community Descriptions of a High Latitude Coral Reef, Florida, USA

Fisheries independent data on relatively unstudied nekton communities were used to explore the efficacy of new tools to be applied in the investigation of shallow coastal coral reef habitats. These data obtained through concurrent diver visual and acoustic surveys provided descriptions of spatial community distribution patterns across seasonal temporal scales in a previously undocumented region. Fish density estimates by both diver and acoustic methodologies showed a general agreement in ability to detect distributional patterns across reef tracts, though magnitude of density estimates were different. Fish communities in southeastern Florida showed significant trends in spatial distribution and seasonal abundance, with higher estimates of biomass obtained in the dry season. Further, community composition shifted across reef tracts and seasons as a function of the movements of several key reef species.

The adoption of retail electronic commerce: an empirical investigation

The purpose of this study was to empirically investigate the adoption of retail electronic commerce (REC). REC is a business transaction which takes place over the Internet between a casual consumer and a firm. The consumer has no long-term relationship with the firm, orders a good or service, and pays with a credit card. To date, most REC applications have not been profitable. To build profitable REC applications a better understanding of the system's users is required. The research model hypothesizes that the level of REC buying is dependent upon the Buying Characteristics of Internet Use and Search Experience plus the Channel Characteristics of Beliefs About Internet Vendors and Beliefs About Internet Security. The effect of these factors is modified by Time. Additional research questions ask about the different types of REC buyers, the differences between these groups, and how these groups evolved over time. To answer these research questions I analyzed publically available data collected over a three-year period by the Georgia Institute of Technology Graphics and Visualization Unit over the Internet. Findings indicate the model best predicts Number of Purchases in a future period, and that Buyer Characteristics are most important to this determination. Further, this model is evolving over Time making Buyer Characteristics predict Number of Purchases better in more recent survey administrations. Buyers clustered into five groups based on level of buying and move through various levels and buy increasing Number of Purchases over time. This is the first large scale research project to investigate the evolution of REC. This implications are significant. Practitioners with casual consumer customers need to deploy a finely tuned REC strategy, understand their buyers, capitalize on the company reputation on the Internet, install an Internet-compatible infrastructure, and web-enable order-entry/inventory/fulfillment/ shipping applications. Researchers might wish to expand on the Buyer Characteristics of the model and/or explore alternative dependent variables. Further, alternative theories such as Population Ecology or Transaction Cost Economics might further illuminate this new I.S. research domain.

A heuristic algorithm to generate test program sequences for moving probe electronic test equipment

The electronics industry, is experiencing two trends one of which is the drive towards miniaturization of electronic products. The in-circuit testing predominantly used for continuity testing of printed circuit boards (PCB) can no longer meet the demands of smaller size circuits. This has lead to the development of moving probe testing equipment. Moving Probe Test opens up the opportunity to test PCBs where the test points are on a small pitch (distance between points). However, since the test uses probes that move sequentially to perform the test, the total test time is much greater than traditional in-circuit test. While significant effort has concentrated on the equipment design and development, little work has examined algorithms for efficient test sequencing. The test sequence has the greatest impact on total test time, which will determine the production cycle time of the product. Minimizing total test time is a NP-hard problem similar to the traveling salesman problem, except with two traveling salesmen that must coordinate their movements. The main goal of this thesis was to develop a heuristic algorithm to minimize the Flying Probe test time and evaluate the algorithm against a "Nearest Neighbor" algorithm. The algorithm was implemented with Visual Basic and MS Access database. The algorithm was evaluated with actual PCB test data taken from Industry. A statistical analysis with 95% C.C. was performed to test the hypothesis that the proposed algorithm finds a sequence which has a total test time less than the total test time found by the "Nearest Neighbor" approach. Findings demonstrated that the proposed heuristic algorithm reduces the total test time of the test and, therefore, production cycle time can be reduced through proper sequencing.

Information systems to support decision-making in construction owner organizations : a data warehousing approach

Construction organizations typically deal with large volumes of project data containing valuable information. It is found that these organizations do not use these data effectively for planning and decision-making. There are two reasons. First, the information systems in construction organizations are designed to support day-to-day construction operations. The data stored in these systems are often non-validated, nonintegrated and are available in a format that makes it difficult for decision makers to use in order to make timely decisions. Second, the organizational structure and the IT infrastructure are often not compatible with the information systems thereby resulting in higher operational costs and lower productivity. These two issues have been investigated in this research with the objective of developing systems that are structured for effective decision-making. A framework was developed to guide storage and retrieval of validated and integrated data for timely decision-making and to enable construction organizations to redesign their organizational structure and IT infrastructure matched with information system capabilities. The research was focused on construction owner organizations that were continuously involved in multiple construction projects. Action research and Data warehousing techniques were used to develop the framework. One hundred and sixty-three construction owner organizations were surveyed in order to assess their data needs, data management practices and extent of use of information systems in planning and decision-making. For in-depth analysis, Miami-Dade Transit (MDT) was selected which is in-charge of all transportation-related construction projects in the Miami-Dade county. A functional model and a prototype system were developed to test the framework. The results revealed significant improvements in data management and decision-support operations that were examined through various qualitative (ease in data access, data quality, response time, productivity improvement, etc.) and quantitative (time savings and operational cost savings) measures. The research results were first validated by MDT and then by a representative group of twenty construction owner organizations involved in various types of construction projects.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Heterogeneous data source access for mobile devices

The mediator software architecture design has been developed to provide data integration and retrieval in distributed, heterogeneous environments. Since the initial conceptualization of this architecture, many new technologies have emerged that can facilitate the implementation of this design. The purpose of this thesis was to show that a mediator framework supporting users of mobile devices could be implemented using common software technologies available today. In addition, the prototype was developed with a view to providing a better understanding of what a mediator is and to expose issues that will have to be addressed in full, more robust designs. The prototype developed for this thesis was implemented using various technologies including: Java, XML, and Simple Object Access Protocol (SOAP) among others. SOAP was used to accomplish inter-process communication. In the end, it is expected that more data intensive software applications will be possible in a world with ever-increasing demands for information.

A mathematical resolution to log transformations and the binning effect in applied processing of data in flow cytometry

This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as "histogram binning" inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation.