Organizational Knowledge Sharing Culture and KMS Effectiveness

Organizations are increasingly adopting Knowledge Management Systems (KMS) to realize firm and operational level benefits. Many KMS fail to yield desired outcomes due to the lack of understanding of the antecedents of successful KMS. Prior studies have established organizational culture as a key antecedent of successful KM. This study investigates the relationship between KMS effectiveness, in terms of its impact on performance, and organizations’ knowledge culture. We develop a model of organizational knowledge processes and employ simulations to examine how the cultural values that govern the employees’ knowledge seeking and sharing propensities influence the impact of KMS on decision making performance. We find that knowledge seeking propensities have a greater influence on KMS effectiveness than knowledge sharing propensities. We also find organizational cultures that foster such knowledge sharing behaviors can expect greater and sustainable performance gains if proactive knowledge seeking is incorporated into work processes

The Economic Implications of Privacy Dark Patterns (PDPs)

This study investigates the economic implications of privacy dark patterns (PDPs) through which firms ``wisely\u27\u27 play privacy games. It is believed that PDPs advantage firms by deceiving consumers. However, it could also hinder firms\u27 credibility. Thus, we aim to examine whether PDPs always benefit firms and hurt consumers. We also seek to answer whether market forces are sufficient to keep PDPs at relatively low levels. Our results show that PDPs make users weakly worse off and the seller weakly better off. Nevertheless, the seller has incentives to not utilize any PDPs when users\u27 privacy cost is high, and the ratio of privacy concern and search cost is either too high or too low under which market shrinkage effect dominates market division effect. Finally, we show that a welfare maximizing social planner would allow the presence of PDPs when users\u27 privacy cost is sufficiently low

Learning and Forgetting Curves in Software Development: Does Type of Knowledge Matter?

What type of knowledge, among domain, technology, and methodology knowledge, is most influential to the performance of software development? We answer to this question by empirically investigating the learning and forgetting curves in software development using an extensive archival data set of software development projects in an IT service company. We find that prior experiences with the same methodology or technology have a stronger impact on software project performance than those in the same application domain. Furthermore, our results show that methodology knowledge is more easily forgotten than domain or technology knowledge. Our findings provide managerial implications not only to the development of knowledge and skills, but also to other organizational issues in software development such as project team staffing and career development

Review of Research on Human Trust in Artificial Intelligence

Artificial Intelligence (AI) represents today\u27s most advanced technologies that aim to imitate human intelligence. Whether AI can successfully be integrated into society depends on whether it can gain users’ trust. We conduct a comprehensive review of recent research on human trust in AI and uncover the significant role of AI’s transparency, reliability, performance, and anthropomorphism in developing trust. We also review how trust is diversely built and calibrated, and how human and environmental factors affect human trust in AI. Based on the review, the most promising future research directions are proposed

KNOWLEDGE OVERLAP, TASK INTERDEPENDENCE, AND TRUST IN IS DEVELOPMENT

Information systems development (ISD) is fundamentally a search process by which the team seeks to find an optimal system configuration that produces the highest performance. As information systems are embodiments of business-domain knowledge and technical knowledge, ISD requires both. The business unit is ultimately responsible for making business design choices whereas the IS unit is largely responsible for making technical design choices. Complexity in ISD arises when these design choices are interdependent. We argue that knowledge overlaps between business and IS play an important role in the ISD process. Using an NK fitness landscapes model of ISD, this research investigates how knowledge overlaps influence ISD performance (1) when the level of interdependencies among design choices varies, (2) for different distributions of within-unit and between-unit interdependencies, (3) when between-unit interdependencies are balanced or skewed, and (4) when inter-unit trust exists or doesn’t. We report the results of a simulation study and discuss their implications and insights

Learning from Prior Experience: An Empirical Study of Serial Entrepreneurs in IT-enabled Crowdfunding

Crowdfunding has gained momentum in recent years. Although an increasing amount of research has been devoted to this domain, the dynamics of this phenomenon has yet to be fully studied. The current study strives to bridge this gap by examining the impacts of prior experiences from serial entrepreneurs’ perspective. Drawing on organizational learning theory, we theorize about the differential effects from several experience dimensions: direct vs. indirect experiences, successful vs. failed experiences, experience richness and diversity of prior experiences. Employing a panel-level analysis approach, we document positive effects of both direct and indirect learning. However, the successful, rich and diverse experience do not always seem to facilitate learning and consequently lead to enhanced performance. Our study applies the organizational learning theory to the crowdfunding context to extend the existing crowdfunding literature in information systems by investigating the dynamics across campaigns. We also provide practical implications for entrepreneurs and platform operators

The Role of Project Modularity in Information Systems Development

Recent surveys have shown that ISD project success rates are particularly low. Organizations are applying a wide array of information systems development methodologies (ISDMs) -- both plan-based and agile, such as waterfall, scrum and XP -- to improve information systems development (ISD) performance. However, as ISD projects often have different characteristics such as size, scope and complexity, prior studies have been focused on helping organizations better choose an ISDM for projects. Nevertheless, prior research has not taken into consideration the notion of problem modularity of ISD projects. In this study, we utilize the NK fitness landscapes model to computationally examine via computer simulations the effects of problem modularity alongside various project environmental factors, and aim to answer the question: under various environmental factors, which ISDM should an ISD team adopt under various degree of problem modularity

Meta-Organizational Learning Through Digital Consensus

Blockchain technology has enabled the emergence of decentralized autonomous organizations (DAOs) with consensus-based governance. Staking governs DAOs instead of centralized authorities. As a new organizing form, DAOs require careful theoretical consideration. We conceptualize the vehicle of consensus-based governance as digital consensus. Using an agent-based simulation model, this paper aims to extend meta-organization theory to incorporate an organizational learning perspective. We benchmark the DAOs using two well-established organizing forms, namely autonomous and hierarchical organizations. We find that hierarchies outperform DAOs in static environments, whereas DAOs outperform hierarchies in turbulent environments, with autonomies only excelling with intensive experimentation. Our analyses allow us to characterize DAOs as evolving through a staggered process of polarization and homogenization, as opposed to autonomies\u27 continuous polarization and hierarchies\u27 continuous homogenization. Such a staggered process can be affected by several factors (e.g., voting thresholds, token asymmetry, and contributor incentives)

WILL THEY STILL PAY? A STUDY OF CONSUMER BEHAVIOR IN AN UNMANNED RETAIL ENVIRONMENT

An unmanned retail shelf is a new retail format made possible by the advance in mobile internet and digital payment technologies. With drastically reduced personnel costs and upfront equipment investment, unmanned retail shelves promise the potential of deeper penetration into more convenient locations for consumers. However, a lack of onsite staff can also mean that unmanned retail shelves are more vulnerable to incidences of theft as compared to traditional stores. We investigate the impact of formal and informal surveillance technology in the context of an unmanned retail environment. By investigating the impact of surveillance technology on consumer behavior outcomes such as theft rate, approach rate, and conversion rate, we hope to better understand if surveillance technologies live up to the promises of improving net economic outcomes by delivering better security