SUSTAINABILITY IN PRIVATE HOUSEHOLDS - INVESTIGATING ACCEPTANCE OF SMART ENERGY APPS

As the use phase of buildings produces a substantial negative environmental impact, mechanisms to guide individuals towards more sustainable energy consumption are of interest. Smart energy apps which constantly monitor energy consumption and provide energy reduction recommendations to private households are a promising tool to tackle this issue. However, as little is known about factors driving their adoption, it remains unclear whether their potential can be leveraged. Against this backdrop, this study derives a technology acceptance model for smart energy apps which builds on a quantitative survey with 300 participants and the partial least squares approach. The results highlight personal innovativeness and environmental norms as additional acceptance factors. Our study points at the importance of personality traits and individual beliefs in technology adoption research, unveils potential levers for IS to drive adoption, and provides guidance to smart energy app designers

Farm Life in the City - A Taxonomy for Smart Urban Agriculture

With more than half of the global population living in cities, current food production has reached sustainability limits. Urban agriculture has moved from an issue at the edge of public discourse to its center to feed future city dwellers. However, cities are hostile for terrestrial life, jeopardizing the availability of important primary resources, such as air, water, or soil. While smart technologies on traditional farms have accelerated the past years (e.g., autonomous tractors), we know little about their potential and applicability in urban areas. Until today, we have little theoretical insights into smart urban agriculture. We offer a multi-layer taxonomy of smart urban agriculture technologies that contributes to the descriptive knowledge in this field while also elucidating the impact on the transformation of cities towards sustainability

The Power of Related Articles – Improving Fake News Detection on Social Media Platforms

Social media is increasingly used as a platform for news consumption, but it has also become a breeding ground for fake news. This serious threat poses significant challenges to social media providers, society, and science. Several studies have investigated automated approaches to fighting fake news, but little has been done to improve fake news detection on the users’ side. A simple but promising approach could be to broaden users\u27 knowledge to improve the perceptual process, which will improve detection behavior. This study evaluates the impact of a digital nudging approach which aims to fight fake news with the help of related articles. 322 participants took part in an online experiment simulating the Facebook Newsfeed. In addition to a control group, three treatment groups were exposed to different combinations of related articles. Results indicate that the presence of controversial related articles has a positive influence on the detection of fake news

EFFECTS OF DIGITAL TRANSFORMATION ON SOCIAL SUSTAINABILITY – AN EFFECT PATH PERSPECTIVE

Although on top of research and practice agendas, digital transformation is still challenging, but promising in addressing economic and ecologic sustainability. However, we lack understanding of the effects of digital transformation on social sustainability and vice versa. Given the relevance of human-centred challenges during digital transformation, a better understanding of the effects of digital transformation on social sustainability is needed. To provide such holistic understanding, we present two effect path models that reflect the effects of digital transformation on social sustainability in the fields of health, education, and equality. Building on a structured literature review and a case study, we find education at the centre of two circular relationships affecting health and equality and highlight the duality of social sustainability as an effect and a driver of digital transformation. Thus, we contribute novel perspectives on digital transformation for social sustainability and aim at inspiring practitioners to foster intra-organisational social sustainability

How to prevent technostress at the digital workplace: a Delphi study

Technostress is a rising issue in the changing world of digital work. Technostress can cause severe adverse outcomes for individuals and organizations. Thus, organizations face the moral, legal, and economic responsibility to prevent employees’ excessive technostress. As technostress develops over time, it is crucial to prevent it throughout the process of its emergence instead of only reacting after adverse outcomes occur. Contextualizing the Theory of Preventive Stress management to technostress, we synthesize and advance existing knowledge on inhibiting technostress. We develop a set of 24 technostress prevention measures from technostress inhibitor literature, other technostress literature, and based on qualitative and quantitative contributions from a Delphi study. Based on expert feedback, we characterize each measure and, where possible, assess its relevance in addressing specific technostressors. Our paper contributes to research by transferring the Theory of Preventive Stress Management into the context of technostress and presenting specific measures to prevent technostress. This offers a complementary view to technostress inhibitors by expanding the theoretical grounding and adding a time perspective through the implementation of primary, secondary, and tertiary prevention measures. For practice, we offer a comprehensive and applicable overview of measures organizations can implement to prevent technostress

The Cards and Lottery Task: Validation of a New Paradigm Assessing Decision Making Under Risk in Individuals With Severe Obesity

Background: A growing body of research demonstrated impaired executive functions in individuals with severe obesity, including increased sensitivity to reward and impulsive decision making under risk conditions. For the assessment of decision making in patients with severe obesity, studies widely used the Iowa Gambling Task (IGT) or the Delay Discounting Task (DDT), which cover short-term or long-term consequences of decisions only. A further development originating from the field of addiction research is the Cards and Lottery Task (CLT), in which each decision made has conflicting immediate and longterm consequences at the same time. The present study aimed to validate the CLT in individuals with severe obesity. Methods: Patients with severe obesity (N = 78, 67% women, 42.9 ± 10.4 years old, body mass index of 48.1 ± 8.3 kg/m2) were included. Convergent validity was evaluated using the computerized Delay Discounting Task and well-established self-report questionnaires assessing different aspects of impulsivity. For discriminant validity, CLT performance was compared between symptom groups characterized by high versus low impulsivity. The task’s clinical validity was evaluated based on associations with general and eating disorder psychopathology, and body mass index. Test-retest reliability was determined by administering the CLT in n = 31 participants without weight-loss treatment one year later. The task’s sensitivity to change due to weight loss was evaluated by retesting n = 32 patients one year after receiving obesity surgery. Results: The number of advantageous decisions in the CLT was significantly positively associated with delay discounting and effortful control, and significantly negatively correlated with behavioral impulsivity. CLT performance differed significantly between individuals with and without symptoms of attention-deficit/hyperactivity disorder and between samples with severe obesity and healthy controls. Clinically, CLT performance was significantly associated with general, but not eating disorder psychopathology. The CLT showed moderate test-retest reliability after one year in weight-stable individuals and was sensitive to change in those undergoing obesity surgery. Conclusions: This study identified the CLT to be a highly promising, new complex measure of short- and long-term decision making with good reliability and validity in individuals with severe obesity. Future studies should assess its association with the IGT and predictive value for real-life health behavior

Changes in visual attention towards food cues after obesity surgery: An eye-tracking study

Research documented the effectiveness of obesity surgery (OS) for long-term weight loss and improvements in medical and psychosocial sequelae, and general cognitive functioning. However, there is only preliminary evidence for changes in attentional processing of food cues after OS. This study longitudinally investigated visual attention towards food cues from pre- to 1-year post-surgery. Using eye tracking (ET) and a Visual Search Task (VST), attentional processing of food versus non-food cues was assessed in n = 32 patients with OS and n = 31 matched controls without weight-loss treatment at baseline and 1-year follow-up. Associations with experimentally assessed impulsivity and eating disorder psychopathology and the predictive value of changes in visual attention towards food cues for weight loss and eating behaviors were determined. During ET, both groups showed significant gaze duration biases to non-food cues without differences and changes over time. No attentional biases over group and time were found by the VST. Correlations between attentional data and clinical variables were sparse and not robust over time. Changes in visual attention did not predict weight loss and eating disorder psychopathology after OS. The present study provides support for a top-down regulation of visual attention to non-food cues in individuals with severe obesity. No changes in attentional processing of food cues were detected 1-year post-surgery. Further studies are needed with comparable methodology and longer follow-ups to clarify the role of biased visual attention towards food cues for long-term weight outcomes and eating behaviors after OS