Customer relationship management: A content analysis of issues and best practices

This dissertation is a study of customer relationship management theory and practice. Customer Relationship Management (CRM) is a business strategy whereby companies build strong relationships with existing and prospective customers with the goal of increasing organizational profitability. It is also a learning process involving managing change in processes, people, and technology. CRM implementation and its ramifications are also not completely understood as evidenced by the high number of failures in CRM implementation in organizations and the resulting disappointments. ^ The goal of this dissertation is to study emerging issues and trends in CRM, including the effect of computer software and the accompanying new management processes on organizations, and the dynamics of the alignment of marketing, sales and services, and all other functions responsible for delivering customers a satisfying experience. ^ In order to understand CRM better a content analysis of more than a hundred articles and documents from academic and industry sources was undertaken using a new methodological twist to the traditional method. An Internet domain name (http://crm.fiu.edu) was created for the purpose of this research by uploading an initial one hundred plus abstracts of articles and documents onto it to form a knowledge database. Once the database was formed a search engine was developed to enable the search of abstracts using relevant CRM keywords to reveal emergent dominant CRM topics. The ultimate aim of this website is to serve as an information hub for CRM research, as well as a search engine where interested parties can enter CRM-relevant keywords or phrases to access abstracts, as well as submit abstracts to enrich the knowledge hub. ^ Research questions were investigated and answered by content analyzing the interpretation and discussion of dominant CRM topics and then amalgamating the findings. This was supported by comparisons within and across individual, paired, and sets-of-three occurrences of CRM keywords in the article abstracts. ^ Results show that there is a lack of holistic thinking and discussion of CRM in both academics and industry which is required to understand how the people, process, and technology in CRM impact each other to affect successful implementation. Industry has to get their heads around CRM and holistically understand how these important dimensions affect each other. Only then will organizational learning occur, and overtime result in superior processes leading to strong profitable customer relationships and a hard to imitate competitive advantage. ^

Latin America and the Caribbean in 2011 and Beyond: A conversation among Latin America and Caribbean Specialists.

For the first time in more than fifty years, the domestic and external conflicts in Latin America and the Caribbean (LAC) are not primarily ideological in nature. Democracy continues to thrive and its promise still inspires hope. In contrast, the illegal production, consumption, and trading of drugs – and its links to criminal gangs and organizations – represent major challenges to the region, undermining several States’ already weak capacity to govern. While LAC macroeconomic stability has remained resilient, illegal economies fill the region, often offering what some States have not historically been able to provide – elements of human security, opportunities for social mobility, and basic survival. Areas controlled by drug trafficking organizations (DTOs) are now found in Central America, Mexico, and the favelas of Rio de Janeiro and São Paulo, reflecting their competition for land routes and production areas. Cartels such as La Familia, Los Zetas, and Primeiro Comando da Capital (PCC-Brazil), among others, operate like trade and financial enterprises that manage millions of dollars and resources, demonstrating significant business skills in adapting to changing circumstances. They are also merciless in their application of violence to preserve their lucrative enterprises. The El Salvador-Guatemala-Honduras triangle in Central America is now the most violent region in the world, surpassing regions in Africa that have been torn by civil strife for years. In Brazil’s favelas and Guatemala’s Petén region, the military is leaving the barracks again; not to rule, however, but to supplement and even replace the law enforcement capacity of weak and discredited police forces. This will challenge the military to apply lessons learned during the course of their experience in government, or from the civil wars that plagued the region for nearly 50 years during the Cold War. Will they be able to conduct themselves according to the professional ethics that have been inculcated over the past 20 years without incurring violations of human rights? Belief in their potential to do good is high according to many polls as the Armed Forces still enjoy a favorable perception in most societies, despite frequent involvement in corruption. Calling them to fight DTOs, however, may bring them too close to the illegal activities they are being asked to resist, or even rekindle the view that only a “strong hand” can resolve national troubles. The challenge of governance is occurring as contrasts within the region are becoming sharper. There is an increasing gap between nations positioned to surpass their “developing nation” status and those that are practically imploding as the judicial, political and enforcement institutions fall further into the quagmire of illicit activities. Several South American nations are advancing their political and economic development. Brazil in particular has realized macro-economic stability, made impressive gains in poverty reduction, and is on track to potentially become a significant oil producer. It is also an increasingly influential power, much closer to the heralded “emerging power” category that it aspired to for most of the 20th century. In contrast, several Central American States have become so structurally deficient, and have garnered such limited legitimacy, that their countries have devolved into patches of State controlled and non-State-controlled territory, becoming increasingly vulnerable to DTO entrenchment. In the Caribbean, the drug and human trafficking business also thrives. Small and larger countries are experiencing the growing impact of illicit economies and accompanying crime and violence. Among these, Guyana and Suriname face greater uncertainty, as they juggle both their internal affairs and their relations with Brazil and Venezuela. Cuba also faces new challenges as it continues focusing on internal rather than external affairs and attempts to ensure a stable leadership succession while simultaneously trying to reform its economy. Loosening the regime’s tight grip on the economy while continuing to curtail citizen’s civil rights will test the leadership’s ability to manage change and prevent a potential socio-economic crisis from turning into an existential threat. Cuba’s past ideological zest is now in the hands of Venezuela’s President Hugo Chavez, who continues his attempts to bring the region together under Venezuelan leadership ideologically based on a “Bolivarian” anti-U.S. banner, without much success. The environment and natural disasters will merit more attention in the coming years. Natural events will produce increasing scales of destruction as the States in the region fail to maintain and expand existing infrastructure to withstand such calamities and respond to their effects. Prospects for earthquakes, tsunamis, and hurricanes are high, particularly in the Caribbean. In addition, there are growing rates of deforestation in nearly every country, along with a potential increase in cross-sector competition for resources. The losers might be small farmers, due to their inability to produce quantities commensurate to larger conglomerates. Regulations that could mitigate these types of situations are lacking or openly violated with near impunity. Indigenous and other vulnerable populations, including African descendants, in several Andean countries, are particularly affected by the increasing extraction of natural resources taking place amongst their terrain. This has led to protests against extraction activities that negatively affect their livelihoods, and in the process, these historically underprivileged groups have transitioned from agenda-based organization to one that is bringing its claims and grievances to the national political agenda, becoming more politically engaged. Symptomatic of these social issues is the region’s chronically poor quality of education that has consistently failed to reduce inequality and prepare new generations for jobs in the competitive global economy, particularly the more vulnerable populations. Simultaneously, the educational deficit is also exacerbated by the erosion of access to information and freedom of the press. The international panorama is also in flux. New security entities are challenging the old establishment. The Union of South American Nations, The South American Defense Council, the socialist Bolivarian Alliance, and other entities seem to be defying the Organization of American States and its own defense mechanisms, and excluding the U.S. And the U.S.’s attention to areas in conflict, namely Iraq, Afghanistan, and Pakistan – rather than to the more stable Latin America and Caribbean – has left ample room for other actors to elbow in. China is now the top trading partner for Brazil. Russian and Iran are also finding new partnerships in the region, yet their links appear more politically inclined than those of China. Finally, the aforementioned increasing commercial ties by LAC States with China have accelerated a return to the preponderance of commodities as sources of income for their economies. The increased extraction of raw material for export will produce greater concern over the environmental impact that is created by the exploitation of natural resources. These expanded trade opportunities may prove counterproductive economically for countries in the region, particularly for Brazil and Chile, two countries whose economic policies have long sought diversification from dependence on commodities to the development of service and technology based industries.

Timeshare Owner Preferences - An Analysis of Program and Service Relationships during Recessionary Times

Since the 1970s various industry studies have indicated that the vacation ownership industry has enjoyed unprecedented growth in unit sales, resort growth, and the number of owners (American Resort Devleopment Association [ARDA], 2007; ARDA, 2009a; ARDA, 2009b). However, due to the recent economic downturn these growth metrics are no longer obtainable. This external impact has caused developers to retrench and therefore reflect upon their existing product and service offerings, financial metrics, and consumer markets (ARDA, 2010a; ARDA 2010b). The crux of these findings indicates that the industry has shifted to maintaining and enhancing product and service offerings as a reaction to changing economic conditions. The findings reported in the body of this manuscript represent product and service preferences as collected from a random data pull of their existing ownership base. The study also revealed current preferences of timeshare owners with relation to services provided and products/amenities offered. Management implications and limitations of the current study are discussed.

Marketing practices and their effectiveness in Taiwan's colleges of technology

The main purpose of this study was to investigate marketing practices in Taiwan's institutions of higher education and their relationship with students' college choice behaviors and attitudes. The study was conducted in 11 Taiwan's colleges of technology. It employed a multistrand conversion mixed model design, consisting of a qualitative and a quantitative strand. Funnel-sequenced interviews were conducted with 19 college administrators and the results were content analyzed using a constant-comparative method. The administrator interview data were also quantitized and used in cluster analysis of the institutions. Questionnaire data were collected from 1474 freshmen students, and analyzed using several univariate and multivariate statistical techniques including factor analysis, MANOVA, and correspondence analysis. ^ Analyses indicated that a weak relationship existed between institutions' marketing intensity and students' college choice. Students did not consider institutions' recruitment activities useful in their college searching process. They also reported little knowledge of their current school when they were deciding to enroll. Data analysis also revealed that students were practically oriented in their college selection. Academic resources, employability after graduation, and tuition were the most important attributes in students' college selection. Parents and students' social network such as friends and high school teachers were significant personal sources in enrollment decisions while institutions' representatives (i.e., recruiters) were considered the least influential. ^ Using cluster analysis, institutions were divided into three groups based on intensity of marketing efforts. Multivariate analysis of variance did not reveal significant differences between the college choice behaviors and attitudes of students who entered these three types of institutions. ^ Content analysis of the administrators' interviews indicated that the majority of them practiced passive marketing. This was primarily as a result of resistance to active marketing, lack of leadership commitment, insufficient financial and human resources, little faculty involvement, and inexperience in marketing. In comparison to public institutions, private institutions showed a more favorable attitude towards marketing concepts. They were well advanced in their recruitment activities while public schools were relatively hesitant to use marketing. Curriculum issues were not well represented in marketing activities and did not seem to be impacted by marketing needs. Based on the analysis of qualitative and quantitative data, it can be concluded that in these colleges, curriculum was more driven by commercial and industrial interest than by students' demands. ^ Theoretical, policy, and methodological implementation of the results were discussed. ^

Experimental analysis of soil and dust stabilizers for controlling displacement of contaminated soils by wind tunnel experiments

During the remediation of burial grounds at the US Department of Energy's (DOE's) Hanford Site in Washington State, the dispersion of contaminated soil particles and dust is an issue that is faced by site workers on a daily basis. This contamination problem is even more of a concern when one takes into account the semi-arid characteristics of the region where the site is located. To mitigate this problem, workers at the site use a variety of engineered methods to minimize the dispersion of contaminated soil and dust (i.e. use of water and/or suppression agents that stabilizes the soil prior to soil excavation, segregation, and removal activities). A primary contributor to the dispersion of contaminated soil and dust is wind soil erosion. The erosion process occurs when the wind speed exceeds a certain threshold value which depends on a number of factors including wind force loading, particle size, surface soil moisture, and the geometry of the soil. Thus under these circumstances, the mobility of contaminated soil and generation and dispersion of particulate matter are significantly influenced by these parameters. This dependence of soil and dust movement on threshold shear velocity, fixative dilution and/or application rates, soil moisture content, and soil geometry were studied for Hanford's sandy soil through a series of wind tunnel experiments, laboratory experiments and theoretical analysis. In addition, the behavior of plutonium (Pu) powder contamination in the soil was studied by introducing a Pu simulant (cerium oxide). The results showed that soil dispersion and PM10 concentrations decreased with increasing soil moisture. Also, it was shown that the mobility of the soil was affected by increasing wind velocity. It was demonstrated that the use of fixative products greatly decreased the amount of soil and PM10 concentrations when exposed to varying wind conditions. In addition, it was shown that geometry of the soil sample affected the velocity profile and calculation of roughness surface coefficient when comparing round and flat soil samples. Finally, threshold shear velocities were calculated for soil with flat surface and their dependency on surface soil moisture was demonstrated. A theoretical framework was developed to explain these dependencies.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

Comparative Analysis of State and Non-State Higher Educational Institutions in Terms of their Adaptation to New Societal Conditions in Post-Soviet Russia

The present paper investigates post-Soviet non-state and state higher educational institutions in terms of students’ perceptions of school curriculum, quality of teaching, available educational resources and overall organization in their higher educational institutions.

Quality of life and application of the transtheoretical model to diabetes self -management behaviors in older adults with type 2 diabetes

One in five adults 65 years and older has diabetes. Coping with diabetes is a lifelong task, and much of the responsibility for managing the disease falls upon the individual. Reports of non-adherence to recommended treatments are high. Understanding the additive impact of diabetes on quality of life issues is important. The purpose of this study was to investigate the quality of life and diabetes self-management behaviors in ethnically diverse older adults with type 2 diabetes. The SF-12v2 was used to measure physical and mental health quality of life. Scores were compared to general, age sub-groups, and diabetes-specific norms. The Transtheoretical Model (TTM) was applied to assess perceived versus actual behavior for three diabetes self-management tasks: dietary management, medication management, and blood glucose self-monitoring. Dietary intake and hemoglobin A1c values were measured as outcome variables. Utilizing a cross-sectional research design, participants were recruited from Elderly Nutrition Program congregate meal sites (n = 148, mean age 75). ^ Results showed that mean scores of the SF-12v2 were significantly lower in the study sample than the general norms for physical health (p < .001), mental health (p < .01), age sub-group norms (p < .05), and diabetes-specific norms for physical health (p < .001). A multiple regression analysis found that adherence to an exercise plan was significantly associated with better physical health (p < .001). Transtheoretical Model multiple regression analyses explained 68% of the variance for % Kcal from fat, 41% for fiber, 70% for % Kcal from carbohydrate, and 7% for hemoglobin A 1c values. Significant associations were found between TTM stage of change and dietary fiber intake (p < .01). Other significant associations related to diet included gender (p < .01), ethnicity (p < .05), employment (p < .05), type of insurance (p < .05), adherence to an exercise plan (p < .05), number of doctor visits/year ( p < .01), and physical health (p < .05). Significant associations were found between hemoglobin A1c values and age ( p < .05), being non-Hispanic Black (p < .01), income (p < .01), and eye problems (p < .05). ^ The study highlights the importance of the beneficial effects of exercise on quality of life issues. Furthermore, application of the Transtheoretical Model in conjunction with an assessment of dietary intake may be valuable in helping individuals make lifestyle changes. ^

The relationship of managers' self -reported leadership practices and their spirituality

The role of spirituality in leadership in business and other organizations has gained growing recognition. The purpose of this study was to explore the relationship between spirituality and nine selected transformational leadership practices. Community leaders (N = 138) in business, education, and other professions who were graduates of a 10-week leadership program, Leadership Fort Lauderdale, from 1994 to 2004 completed the Spirituality Assessment Scale (SAS), the Leadership Practices Inventory (LPI), and four transformational leadership items of the Multifactor Leadership Questionnaire (MLQ). ^ The predictor variables were participants' scores on the LPI and MLQ. The criterion variable was their score on the SAS. Stepwise multiple regression analysis was used to test the hypothesis: Is there a combination of nine selected transformational leadership practices that would account for a significant portion of the variance of each of two spirituality measures? The Definitive and Correlated dimensions and Total spirituality score of the SAS were used in the analysis. ^ Results showed that two of the LPI leadership practices were significantly related to spirituality. The variable Inspiring a Shared Vision accounted for 10% of the variance of the SAS Definitive dimension. The variable Encouraging the Heart accounted for 30% of the variance of the Correlated dimension. For the Total spirituality score, two models were revealed. In the first model, Encouraging the Heart accounted for 28% of the variance of the total spirituality score. In the second model, Encouraging the Heart and Inspiring a Shared Vision together accounted for 31% of the total spirituality score. None of the transformational leadership practices from the MLQ were significantly related to spirituality. ^ The data partially support the hypothesis: two of the nine leadership variables did in combination correlate with leaders' spirituality. The results also support at least a partial relationship between spirituality and certain transformational leadership practices among leaders in various spheres, such as education, business, and other professions. ^

The Life and Work of Severo Sarduy: A Conversation with Mercedes Sarduy and Catalina Quesada

This flyer promotes the event "The Life and Work of Severo Sarduy: A Conversation with Mercedes Sarduy and Catalina Quesada".

Text analytics of social media: Sentiment analysis, event detection and summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. ^ Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. ^ In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data. ^

A content analysis of food and nutrition television advertisements

Television (TV) reaches more people than any other medium which makes it an important source of health information. Since TV ads often offer information obliquely, this study investigated implied health messages found in food and nutrition TV ads. The goals were to determine the proportion of food and nutrition ads among all TV advertising and to use content analysis to identify their implied messages and health claims. A randomly selected sample of TV ads were collected over a 28-day period beginning May 8, 1987. The sample contained 3547 ads; 725 (20%) were food-related. All were analyzed. About 10% of food-related TV ads contained a health claim. Twenty-five representative ads of the 725 food ads were also reviewed by 10 dietitians to test the reliability of the instrument. Although the dietitians agreed upon whether a health claim existed in a televised food ad, their agreement was poor when evaluating the accuracy of the claim. The number of food-related ads dropped significantly on Saturday, but the number of alcohol ads rose sharply on Saturday and Sunday. Snack ads were shown more often on Thursday, but snack commercials were also numerous on Saturday morning and afternoon, as were cereal ads. Ads for snack foods accounted for the greatest proportion of ads (20%) while fast food accounted for only 7%. Alcohol constituted about 9% of all food and nutrition ads.

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Elemental Analysis of Glass and Ink by Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) and Laser Induced Breakdown Spectroscopy (LIBS)

The necessity of elemental analysis techniques to solve forensic problems continues to expand as the samples collected from crime scenes grow in complexity. Laser ablation ICP-MS (LA-ICP-MS) has been shown to provide a high degree of discrimination between samples that originate from different sources. In the first part of this research, two laser ablation ICP-MS systems were compared, one using a nanosecond laser and another a femtosecond laser source for the forensic analysis of glass. The results showed that femtosecond LA-ICP-MS did not provide significant improvements in terms of accuracy, precision and discrimination, however femtosecond LA-ICP-MS did provide lower detection limits. In addition, it was determined that even for femtosecond LA-ICP-MS an internal standard should be utilized to obtain accurate analytical results for glass analyses. In the second part, a method using laser induced breakdown spectroscopy (LIBS) for the forensic analysis of glass was shown to provide excellent discrimination for a glass set consisting of 41 automotive fragments. The discrimination power was compared to two of the leading elemental analysis techniques, µXRF and LA-ICP-MS, and the results were similar; all methods generated >99% discrimination and the pairs found indistinguishable were similar. An extensive data analysis approach for LIBS glass analyses was developed to minimize Type I and II errors en route to a recommendation of 10 ratios to be used for glass comparisons. Finally, a LA-ICP-MS method for the qualitative analysis and discrimination of gel ink sources was developed and tested for a set of ink samples. In the first discrimination study, qualitative analysis was used to obtain 95.6% discrimination for a blind study consisting of 45 black gel ink samples provided by the United States Secret Service. A 0.4% false exclusion (Type I) error rate and a 3.9% false inclusion (Type II) error rate was obtained for this discrimination study. In the second discrimination study, 99% discrimination power was achieved for a black gel ink pen set consisting of 24 self collected samples. The two pairs found to be indistinguishable came from the same source of origin (the same manufacturer and type of pen purchased in different locations). It was also found that gel ink from the same pen, regardless of the age, was indistinguishable as were gel ink pens (four pens) originating from the same pack.