Workarounds as generative mechanisms for bottom-up process innovation—Insights from a multiple case study

2023 | Information Systems Journal | Citations: 0

Authors: Bartelheimer, Christian; Wolf, Verena; Beverungen, Daniel

Abstract: Workarounds are goal-driven deviations from the standard operating procedures pe ... Expand

Abstract: Workarounds are goal-driven deviations from the standard operating procedures performed to overcome obstacles constraining day-to-day work. Despite starting as temporary fixes, they can become established across an organisation and trigger the innovation of processes and IT artefacts that can resolve misfits permanently. Although prior research has elicited antecedents and types of workarounds, it is not known how workarounds diffuse in an organisation and, thereby, innovating co-workers' activities, IT artefacts, and organisational structures. The results of our multiple two-year case study provide unique empirical insights into the diffusion of workarounds and how they can act as generative mechanisms for bottom-up process innovation. Collapse

Topics: business process management innovation management business process innovation organization structure business process redesign

Methods: design artifact case study business process modeling qualitative interview qualitative coding

Theories: socio technical theory structuration theory

Expl(AI)ned: The Impact of Explainable Artificial Intelligence on Users’ Information Processing

2023 | Information Systems Research | Citations: 0

Authors: Bauer, Kevin; von Zahn, Moritz; Hinz, Oliver

Abstract: Because of a growing number of initiatives and regulations, predictions of moder ... Expand

Abstract: Because of a growing number of initiatives and regulations, predictions of modern artificial intelligence (AI) systems increasingly come with explanations about why they behave the way they do. In this paper, we explore the impact of feature-based explanations on users’ information processing. We designed two complementary empirical studies where participants either made incentivized decisions on their own, with the aid of opaque predictions, or with explained predictions. In Study 1, laypeople engaged in the deliberately abstract investment game task. In Study 2, experts from the real estate industry estimated listing prices for real German apartments. Our results indicate that the provision of feature-based explanations paves the way for AI systems to reshape users’ sense making of information and understanding of the world around them. Specifically, explanations change users’ situational weighting of available information and evoke mental model adjustments. Crucially, mental model adjustments are subject to the confirmation bias so that misconceptions can persist and even accumulate, possibly leading to suboptimal or biased decisions. Additionally, mental model adjustments create spillover effects that alter user behavior in related yet disparate domains. Overall, this paper provides important insights into potential downstream consequences of the broad employment of modern explainable AI methods. In particular, side effects of mental model adjustments present a potential risk of manipulating user behavior, promoting discriminatory inclinations, and increasing noise in decision making. Our findings may inform the refinement of current efforts of companies building AI systems and regulators that aim to mitigate problems associated with the black-box nature of many modern AI systems. History: Alessandro Acquisti, senior editor; Jason Chan, associate editor. Funding: This work was supported by the Deutsche Forschungsgemeinschaft (DFG) (Projek 449023539), Volkswagen Foundation (ML2MT), and LeibnizInstitute for Financial Research SAFE. Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2023.1199. Collapse

Topics: explainable artificial intelligence artificial intelligence shapley additive explanation local interpretable model agnostic explanation decision making

Methods: F-test regression analysis method experiment field study robustness check

Unveiling the paradox of technostress: Impacts of technology-driven stressors on the elderly's avoidance behaviors

2023 | Information & Management | Citations: 0

Authors: Cheng, Xusen; Huang, Xiaowen; Yang, Bo; Xiao, Yuting

Abstract: This study reveals the paradox of technostress on the elderly due to the large-s ... Expand

Abstract: This study reveals the paradox of technostress on the elderly due to the large-scale COVID testing during the postCOVID-19 period. Drawing upon the stressor-strain-outcomes framework, we examined how technology-driven stressors affect the elderly’s avoidance behaviors. Results indicate that two types of technology-driven stressors exert opposite influences on the elderly’s avoidance behaviors through the mediating effect of technology anxiety. Specifically, the elderly’s technology-driven challenge stressors exert a positive influence on their avoidance behaviors, while the elderly’s technology-driven hindrance stressors exert a negative influence. Moreover, stigma consciousness plays a moderating role in the relationship between the elderly’s technologydriven hindrance stressors and technology anxiety by strengthening the positive influence of the elderly’s technology-driven hindrance stressors on technology anxiety. Our findings deepen the understanding of the good and bad of technostress and provide implications for older adults, technology developers, and the government. Collapse

Topics: smartphone technostress pandemic self efficacy anonymity

Methods: qualitative interview survey SEM tool mixed method qualitative coding

An Action Design Research Study on Responsible Innovation Teaching and Training for Information Systems Students

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: El Idrissi, Sarah Cherki; Corbett, Jacqueline; Mellouli, Sehl

Abstract: While information systems organizations recognize the importance of incorporati ... Expand

Abstract: While information systems organizations recognize the importance of incorporating responsible innovation into their activities, they often face difficulty implementing this practice because employees lack the required knowledge and skills, particularly the capacity for reflexivity and reflection. This paper aims to accelerate responsible innovation teaching and training for information systems students to expedite the process of positive change for sustainability. Using the action design research methodology and the responsible innovation lens, we developed a workshop enabling information systems students to form measurable reflection skills. The workshop evaluation suggests that learning took place and that students are willing to adopt responsible innovation in their future workplaces. A set of design guidelines is proposed to guide further training programs to enhance students' ability to address complex challenges responsibly. This paper answers the call for more impactful information systems research to address societal and environmental challenges and enriches the literature on sustainable social development and business practices. Collapse

Topics: innovation management task complexity personality responsible artificial intelligence digital innovation

Methods: design guideline qualitative interview action design research design science qualitative coding

Chatbot commerce—How contextual factors affect Chatbot effectiveness

2023 | Electronic Markets | Citations: 0

Authors: Hsu, Pei-Fang; Nguyen, Tuan (Kellan); Wang, Chen-Ya; Huang, Pei-Ju

Abstract: The emergence of Chatbots has attracted many firms to sell their merchandise via ... Expand

Abstract: The emergence of Chatbots has attracted many firms to sell their merchandise via chats and bots. Although Chatbots have received tremendous interest, little is understood about how different usage contexts affect Chatbots’ effectiveness in mobile commerce. Due to differences in their nature, not all shopping contexts are suitable for Chatbots. To address this research gap, this study examines how contextual factors (i.e., intrinsic task complexity that embraces shopping task attributes and group shopping environment, and extrinsic task complexity that entails information intensity) affect user perceptions and adoption intentions of Chatbots as recommendation agents in mobile commerce. Applying the lenses of cognitive load theory (CLT) and common ground theory (CGT), we perform an experiment and apply quantitative analytical approaches. The results show that Chatbots are more suitable in the context of one-attribute, information-light, and group-buying tasks, whereas traditional Apps are suitable for multi-attribute, information-intensive, and single-buying scenarios. These findings make important theoretical contributions to the IT adoption literature as well as to CLT and CGT theory by contextualizing the evolving state of Chatbot commerce and providing guidelines for designing better Chatbot user experiences, thereby enhancing user perceptions and adoption intentions. Collapse

Topics: mobile application task complexity electronic commerce technology adoption recommender system

Methods: chatbot experiment qualitative interview chi squared test survey

Theories: cognitive load theory

Do Employees Work Less for Female Leaders? A Multi-Method Study of Entrepreneurial Firms

2023 | Organization Science | Citations: 0

Authors: Kacperczyk, Olenka; Younkin, Peter; Rocha, Vera

Abstract: We propose that female-founded ventures receive a lower amount of employee labor ... Expand

Abstract: We propose that female-founded ventures receive a lower amount of employee labor for equal pay because employees are more likely to decline requests for additional labor by female founders. First, using longitudinal matched employer-employee data covering all founders of new ventures with personnel in Portugal between 2002 and 2012, we confirm that full-time employees contribute fewer regular hours and less overtime work to female-founded firms. Second, using a series of online experiments, we show that this variation in employee labor across female and male-founded firms is partly motivated by a difference in the employee’s expectations of work demands. Specifically, employees perceive female founders’ requests for additional labor to be unfair and more difficult than expected, and both these perceptions explain the lower amount of employee labor supplied in female-founded ventures. Overall, our findings uncover a novel mechanism that helps explain the existence of a gender gap in entrepreneurship beyond the entry stage. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022.1611. Collapse

Topics: entrepreneurship IT career database system productivity missing data

Methods: experiment quantitative observational study theory development survey descriptive statistic

Theories: sociological theory

Toward Identifying the Factors Associated with Conversational Agents’ Performance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Khan, Abdul Kader; Palvia, Prashant

Abstract: With advances in computing and a preference for convenience in completing digit ... Expand

Abstract: With advances in computing and a preference for convenience in completing digital tasks, conversational agents (CAs) have gained widespread popularity throughout the world. However, most of the CAs seem to lack several necessary capabilities to satisfy the users' needs. Our study focused on text-based CAs (also known as chatbots) and examines the factors associated with their performance. The literature on IS success and adoption suggest that various factors related to the technology, users, and tasks can jointly play a role in satisfying user needs. Thus, we adopt a holistic approach to evaluating chatbot performance by identifying chatbot attributes, user attributes, and task attributes and their impact on chatbot performance from the users' view. We conducted interviews with chatbot users and using a qualitative approach, provide a theoretical framework for chatbot performance evaluation. All the interviews were conducted with the users of rule-based chatbots as these are widely used by all sizes of organizations. Collapse

Topics: user satisfaction task complexity privacy digital platform user requirement

Methods: chatbot qualitative interview qualitative content analysis literature study grounded theory

Unemployment and Online Labor: Evidence from Microtasking

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Laitenberger, Ulrich; Viete, Steffen; Slivko, Olga; Kummer, Michael; Borchert, Kathrin; Hirth, Matthias

Abstract: We analyze the relationship between unemployment and the supply of online labor ... Expand

Abstract: We analyze the relationship between unemployment and the supply of online labor for microtasking. Using detailed U.S. data from a large microtasking platform between 2011 and 2015, we study the participation and the number of hours supplied by workers in the U.S. We found that more individuals registered on the platform and completed microtasks as the unemployment level in the commuting zone increased. This effect was strongest in regions with a high share of low-skilled workers. Our analyses of the intensive margin, wage elasticity, and temporal work patterns suggest that the increased participation was likely motivated by an effort to substitute income. Our findings suggest that microtasking platforms are an interesting online labor market for less educated workers. However, we also observed very low retention rates, indicative of a solely transient participation effect. Collapse

Topics: online labor market Facebook task complexity information technology infrastructure accounting

Methods: instrumental variables estimation survey archival research autocorrelation analysis longitudinal research

The effects of knowledge mechanisms on employees' information security threat construal

2023 | Information Systems Journal | Citations: 1

Authors: Mady, Ashraf; Gupta, Saurabh; Warkentin, Merrill

Abstract: Organisations implement a variety of knowledge mechanisms such as information se ... Expand

Abstract: Organisations implement a variety of knowledge mechanisms such as information security education, training and awareness (SETA) programs and information security policies, to influence employees' secure behaviour. Despite increased efforts to provide information systems (IS) security knowledge to employees, data breaches and other security incidents resulting from insider behaviour continue. Recent IS security research, primarily grounded on assumptions of employees' rational assessment of numerous factors, has yielded inconsistent results. Challenging this paradigm, we model secure behaviour on security knowledge mechanisms, which focuses on the multidimensional nature of security knowledge breadth, depth and finesse to represent the full array of managerial levers. We further draw on construal level theory to conceptualise users' perceptual judgements of security messages. Two studies support our model, with the second building on the first. Study 1, an experiment with 312 participants, focused on validating the treatments. Study 2, a survey with 219 participants, validated the entire model. Results showed that our model has significantly more explanatory and predictive power than the orthodox paradigm. Our results have practical implications for optimising the organisation of knowledge mechanisms by emphasising the personal relevance of threats and defining the factors that lead to secure behaviour. We also contribute to the discourse on information security research and provide a template for integrating theories, thus opening new avenues for future research. Collapse

Topics: data security email phishing security policy IT security task complexity

Methods: survey experiment Student's t-test parametric test survey design

Theories: construal level theory security compliance theory

When Do Boards of Directors Contribute to Shareholder Value in Firms Targeted for Acquisition? A Group Information-Processing Perspective

2023 | Organization Science | Citations: 0

Authors: Pavićević, Stevo; Haleblian, Jerayr (John); Keil, Thomas

Abstract: We draw on group information-processing theory to investigate how target boards ... Expand

Abstract: We draw on group information-processing theory to investigate how target boards of directors may contribute to target value capture during the private negotiations phase in acquisitions. We view target boards as information-processing groups and private negotiations as information-processing tasks. We argue that target board meeting frequency is associated with increased processing—gathering, sharing, and analyzing—of acquisition-related information, which improves target bargaining and, ultimately, target value capture. We further posit that this value-enhancing effect of target board meeting frequency is more pronounced when target board composition improves the ability of target boards to process acquisition-related information. Finally, we expect that meeting frequency is more consequential for target bargaining and value capture when acquisition complexity imposes high information-processing demands on the target boards during private negotiations. Empirical evidence from a sample of acquisitions of publicly listed firms in the United States offers support for our group information-processing perspective on board contribution to shareholder value in firms targeted for acquisition. Funding: This work was supported by the Strategy Research Foundation [Dissertation Grant SRF-2015DP-0016]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2022.1643. Collapse

Topics: value creation IT career database system task complexity task productivity

Methods: regression analysis method statistical hypothesis test longitudinal research ordinary least square Kolmogorov-Smirnov test

Theories: information processing theory