Towards a Theory of IS Support-Related Activity

Information systems (IS) support department has become one major source of knowledge for organizational end-users (employees) as organizations increasingly adopt complex and integrated information technologies. Despite its significance to IS post-adoptive use, IS support-related activity remains under-studied. This study aims at developing an integrative conceptualization of IS support-related activity by drawing on IS use and adaptation theory. We conducted an in-depth qualitative study in the organizational support of a new procurement system and analyzed 591 service interactions between IS support personnel and end-users. Our data analysis suggests that IS support-related activity is a multifaceted phenomenon that comprises a set of increasingly complex behaviors, including technology-oriented behaviors, user-oriented behaviors, and activities that IS personnel undertake to adapt to the technology-user-business context. In particular, IS support personnel were found performing three major types of IS support activity -- informating, diagnosing, and boundary-spanning – which were associated with IS use behavior and required different types of knowledge in IS support context. This study contributes to IS literature by developing a comprehensive view of IS support-related activity, extending existing conceptualizations that exclusively focuses on technology or on human agency. The findings highlight the complexity and dynamics in IS post-implementation era, and present an urgent need to evaluate the challenges in and competence required for IS support work

Differentiating the Effect of Cumulative Experience and Learning: A Field Study of Help Desk Support

The phenomenon of learning curves has been widely accepted as a fundamental pattern in organizational behavior. However, few studies focused on understanding the learning curves in professional services. This paper attempted to examine the learning experiences of help desks. The quantitative data of twenty-five educational institutions over five-year period evidenced the learning curve presence in information technology (IT) services context, but failed to demonstrate the variation in learning rates across institutions as anticipated. Qualitative data from our subsequent case studies suggested that institutions adopted similar tools and procedures in their help desk operation, facilitating their learning from past experience. However, help desks differ in their learning from indirect experience. This study applied organizational learning theory to IT services, and contributed to literature by differentiating the effects of cumulative experience and learning from indirect experience. In addition, it provided industry practitioners insights into more effective management of help desk services

Learning in Enterprise System Support: Specialization, Task Type and Network Characteristics

In this paper, we introduce two contingency factors --task type and network characteristics—that examine how individuals learn from experience. We hypothesize that task specialization and variation have positive impacts on IS professionals’ learning from experience. We further hypothesize that this performance effect of learning is contingent upon task type and characteristics of domain-specific knowledge networks. In particular, specialized experience will be more beneficial to learning when a task is a locating task-type or when network centrality is high. In contrast, varied experience will be more beneficial when a task is a diagnosing task-type or when network betweenness is high. The research model will be validated in the context of postimplementation enterprise system support. The study incorporates a social network perspective to study learning by experience, and contributes to the knowledge management field. Findings will provide practical insights on managing IT human capital and improving IS support services

Understanding the Value of Social Media in the NBA’s Digital Communication: A Fan(s)’ Perspective

Social media (SM) has become sports organizations’ most preeminent vehicle to engage with fans and to enhance relationship marketing. Prior studies have mostly focused on the standpoints of sports organizations; less is known about fans’ SM experience and perspective. This study focuses on sports fans’ SM use during a game, and seeks to understand their popular SM uses and gratifications and the effect of individual characteristics. Informed by the uses and gratifications theory (UGT), we analyze survey data of 400 season-ticket holders of a professional NBA team. Our quantitative data analysis suggests that during a game the NBA sports fans use SM for posting on Twitter & Facebook, on Instagram & Snapchat, and checking emails. The less popular uses and gratifications include accessing teams’ website, downloading video, and accessing mobile Apps. These usage behaviors varied by individual age, gender and household income. Research contribution and implications are discussed

Knowledge Transfer in Information Systems Support Community: Network Effects of Bridging and Reaching

This study focuses on two network characteristics of an IS support community – bridging and reaching – and examines their effects on knowledge transfer and IS support professional\u27s productivity. Bridging is studied through Burt’s structural holes (constraint) measure; Reaching is studied through Valente and Foreman’s closeness centrality (radiality) measure. We posit that structural hole access and closeness centrality are positively related to IS support professional’s productivity. To test our hypotheses, we collected archival data comprising 11,409 system usage problem records reported by over 2,000 users during an 11-month post-implementation period of a new enterprise system, SAP/R3, in a large U.S. company. We analyzed the data using social network analysis and analysis of covariance. Our results provide strong support for our hypotheses. Our study offers new insight into traditional arguments on the path-dependency of experience learning and absorptive capacity and suggests several ways for IS professionals to improve their productivity

Barriers to e-Learning During Crisis: A Capital Theory Perspective on Academic Adversity

The unprecedented coronavirus pandemic (COVID-19) presented new, daunting academic adversities to college students, especially those from underserved communities. This study provides a nuanced understanding of underserved students’ adversities in online distance education, based on an in-depth analysis of narratives of 220 students from a minority-serving institution in the United States. Informed by the capital theory, the study revealed six major barriers to e-learning: technical, cultural, environmental, balance, social, and financial barriers, and identified new underlying dimensions. Moreover, the study found that technical barriers are often coupled with other types of barriers and underserved students are more likely to experience multiple learning barriers. A variance model of influencing factors was proposed for e-learning outcomes. The paper highlights new digital divide in e-learning and provides practical implications for educational institutions to support underserved students in overcoming academic adversities and building educational resilience

Introduction to Digital Social Media in Enterprise Minitrack

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Stress and Coping Mechanisms in Gig Work

Advancements in digital technology have given rise to the creation of digital platforms and the growth of gig work. Gig work is a new form of work based on short-term, contract arrangements through the open marketplaces on digital platforms (Valley, 2000). As a result of the contract-based work arrangement, participants in gig work are more entrepreneurial and individualistic. To be considered gig work, the work must meet the following requirements: platform-related; predominantly microtasks, which are menial, monotonous, and tightly bounded; external contributors are classified by the platforms as independent contractors self-employed status and being evaluated digitally (Howcroft, 2019). In the gig work environment, workers enjoy a sense of autonomy in making job decisions on a digital platform (Deng and Joshi, 2016), but they are also being managed through a micro-level task control (Howcroft, 2019). Instead of having overall work being observed, gig workers found each function and task being monitored. The relations of the platforms working as intermediaries from a job provider to a job seeker are more like an automated job manager where some platforms combine automation with humans (Howcroft, 2019, p. 26). The platforms have created and applied algorithms to manage job listings and work processes. This type of management enables the platforms to meticulously track workers in an optimized manner over a large scale (Howcroft, 2019, p. 30). In the gig work environment, this management style pushes workers to become dependent on computer algorithms for work and performance evaluation. In the cases where a worker is underperforming, the platform puts pressure on the worker by intense supervisory pressure and discipline on the basis of remote covert monitoring of their work (Wood, 2019, p. 62). In addition to benefits, this new gig work opportunity has also brought problems that should be addressed. One of the problems that we find necessary to address is gig workers’ stress condition and coping mechanism. Stress can be defined as antecedent conditions within one\u27s job or the organization which require adaptive responses on the part of the employees (Jex & Beehr, 1991, p. 312). Multiple factors can lead to the gig worker being stressed. Lazarus and Folkman (1984, p. 141) defined coping as constantly changing cognitive and behavioral efforts to manage specific external and/or internal demands that are appraised as taxing or exceeding the resources of the person. It is necessary to understand the best coping mechanism to generate insights to inform key stakeholders in the gig economy, including workers, platform companies, and client organizations. This study has the potential to help gig workers manage or develop a coping mechanism that helps reduce their emotional and physical stress. Based on our data analysis, we were able to identify some important characteristics of gig workers. Workers with different levels of participation in crowdwork were found to be associated differently with their financial stress. Financial stress is defined as an individual concern about his/her ability to earn sufficient income to provide for their basic needs. Furthermore, the data analysis shows gig workers cope with stress by using different strategies, including reaching out, escape, or avoidance. Our next step for this study is to consider additional individual background factors such as gender, age, and financial dependence on gig work platforms. In addition to the qualitative data analysis, we will also use quantitative analysis to understand the behaviors of the gig work participants. Our study will contribute to gig work research by understanding the factors leading to gig work stress and offering insights into the coping mechanisms to help gig workers reduce stress