Business Value of IT-Enabled Call Centers: An Empirical Analysis

Corporate information technology (IT) investments in customer support and service such as CRM systems have been on a steady rise. Of late, the primary interest has shifted toward assessment of returns on these invest- ments. This research attempts to assess the value of IT investments in a customer support setting using a process-level analysis. Given the lack of academic IS research in the area of customer support and value of IT in the service context, this study aims to bridge this gap by building on prior business value of IT literature. In order to identify the contribution of IT in the context of our study, we explicitly control for personnel-specific factors and customer-specific factors. Our findings indicate that IT enabled call centers significantly improve the performance of the customer support process. Further, we also find that the benefits from IT enabled call centers may be higher when the customer-reported problems are complex and difficult to resolve. In addition, we find that both personnel-specific factors and customer-specific factors significantly influence the business benefits from IT in call center and customer support applications

Could Government Measures Crowd Out Grassroots Philanthropy? Empirical Evidence from an Education Crowdfunding Platform

Over the last two decades, grassroots altruism, enabled through platforms such as DonorsChoose.org, has resulted in successful funding of innumerable and essential public school projects across the country. While such channels become critical fundraising mechanisms, there is an unintended possibility of crowding out of these sources by governmental initiatives which aim to shed light on, and address public school resource deficits. In this study, with a focus on major public policy announcements, we examine whether there is an unintended effect of external measures, such as the signing of the Every Student Succeeds Act (ESSA), on grassroots altruism, which is possible to examine on online philanthropy platforms. We surmise that, in such platforms, donors could become complacent and take comfort in the cognizance of an external agency addressing the problems they care about -- we call this the “savior effect”. Importantly, from our analysis of panel data on the platform, we find that the savior effect: (a) results in declined donations toward under-served public school projects on the platform, and (b) makes donations more local, disproportionately impacting schools with high concentrations of low-income and minority students, which receive fewer instructional resources to begin with. Our work has important policy implications for public schools, donor communities, and online fundraising platforms

Determinants of Inspection Effectiveness in Software Development: An Empirical Analysis

Software inspections are formal evaluations of the intermediate work products (artifacts) of the development process. These artifacts are examined to ensure that a high quality work-product is delivered to the testers and ultimately to the end-users of the software product. The crucial role of inspections in determining quality of the software makes it important to assess the effectiveness of inspections. While prior research has identified several factors that influence effectiveness of software inspections, our understanding of the influence of team composition (personnel mix and team size) and the type of the inspected artifact (project plan, requirements specification, design document, code) on effectiveness of inspections is minimal. We develop hypotheses for the factors affecting inspection effectiveness and attempt to validate these hypotheses in a field setting. Our preliminary results show that, during early stages of software development, an increase in the proportion of experienced reviewers (with greater domain experience) is associated with both an increase in the total number of defects discovered in the inspection process as well as an increase in the likelihood of detecting high severity defects. However, during later stages, we find that greater pro- gramming experience is associated with both an increase in the total number of defects discovered in the inspection process as well as an increase in the likelihood of detecting high severity defects. These results have important implications for both practice and research

Disaster Management Through Digital Platforms: Online Crowdfunding Communities Respond to the COVID-19 Pandemic

We study how digital crowdfunding platforms can help replenish the sudden economic deficiencies that accompany a global crisis. Specifically, we examine whether public schools, which suffered severe setbacks during the COVID-19 crisis, were able to generate support from online fundraising communities. We study how the shutdown of schools and the shift to online learning in the United States affected private fundraising on the DonorsChoose.org platform. We find evidence that, after the exogenous shock caused by stay-at-home orders, donations to schools increased and the increased level of concern moves toward high-need schools. Moreover, we find a shift in donation patterns, wherein donors swiftly adapted to renewed priorities and redistributed their resources to immediate needs around digital learning infrastructure. Our findings reveal the pivotal role digital platforms can play in facilitating community resilience during times of crisis

The Role of Electronic Word-of-Mouth on Stakeholders’ Perceptions: Can Online Opinion Impact Managers’ Futures?

The recent advances in information technology have provided new avenues for corporate executives to present themselves to and interact with internal and external stakeholders. We aim to examine the concept that electronic word-of-mouth (eWOM) in the realm of top managers and its consequences on job tenure. Although prior research provides evidence about influence of eWOM on various organizational outcomes, influence on top management career prospects including managerial survivability is not clear. In this study, we are interested in understanding how eWOM about top managers can affect managers’ career prospects. Specifically, we seek to answer two questions. Does eWOM about top managers in social media affect survivability in their current positions? If so, can managers’ participation in online community moderate this relation? We apply text mining techniques on publicly available social media posts about top managers to assess how public opinion influences survivability in their positions

IT Governance and Portfolio Management: An Exploration of the Superior IT Project Investment Portfolios

In this study, we explore the characteristics with the IT project investments for improving the IT portfolio superiority. Our methodology is based on the computational modeling approach. The preliminary findings implicate that a firm could manage to improve on the selectivity, heterogeneity, and scalability in the IT project investments for portfolio selection

Complexity metrics and customer involvement in software development: Implications for managing productivity and quality.

Often, we find that software development is plagued by schedule and cost estimates that are grossly inaccurate, software that is of poor quality, and development productivity that is increasing at a slower rate than the demand for software. This situation has often been termed as the software crisis. This dissertation is composed of three self-contained essays that throws light on some problems related to the software crisis. They address relationships among measures of design complexity in software, conformance quality of the developed software, and innovative process changes such as customer involvement that enable managers and software developers to cope with development challenges. Each essay involves an independent field study in a real-world corporate setting. In the first essay, the primary relationship of interest is the role of design complexity metrics on the quality of the software. We study several hundred modules in a hierarchical structure (created using the object-oriented analysis and design technique) and analyze the link between design complexity metrics in such a setting and conformance quality measured as defects found in modules after development. We find evidence for the relationship between several measures of design complexity and defects. In the second essay, we propose metrics that better represent design complexity in development environments where construction of the software application is through assembly of pre-built modules (components) as opposed to traditional development settings where most modules of an information system are build afresh and in-house. Utilizing data gathered from a field setting, this analysis examines relationships among the proposed design complexity measures, the actual development effort expended in the development of the product, and quality of the end product. While the first and second essay address the product aspect of software development, the third essay focuses on the process aspect. Specifically, we explore the implications of development practices that entail customer involvement, such as activities that help control product-scope and activities that promote iterative customer-team feedback mechanisms, on the productivity and development time of software projects. Through detailed empirical analyses in a field setting, we find that evidence for constructive as well as disruptive influence of customer involvement.Ph.D.ManagementSocial SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/124192/2/3122052.pd

Extracting Actionable Insights from Text Data: A Stable Topic Model Approach

Topic models are becoming a frequently employed tool in the empirical methods repertoire of information systems and management scholars. Given textual corpora, such as consumer reviews and online discussion forums, researchers and business practitioners often use topic modeling to either explore data in an unsupervised fashion or generate variables of interest for subsequent econometric analysis. However, one important concern stems from the fact that topic models can be notorious for their instability, i.e., the generated results could be inconsistent and irreproducible at different times, even on the same dataset. Therefore, researchers might arrive at potentially unreliable results regarding the theoretical relationships that they are testing or developing. In this paper, we attempt to highlight this problem and suggest a potential approach to addressing it. First, we empirically define and evaluate the stability problem of topic models using four textual datasets. Next, to alleviate the problem and with the goal of extracting actionable insights from textual data, we propose a new method, Stable LDA, which incorporates topical word clusters into the topic model to steer the model inference toward consistent results. We show that the proposed Stable LDA approach can significantly improve model stability while maintaining or even improving the topic model quality. Further, employing two case studies related to an online knowledge community and online consumer reviews, we demonstrate that the variables generated from Stable LDA can lead to more consistent estimations in econometric analyses. We believe that our work can further enhance management scholars’ collective toolkit to analyze ever-growing textual data