Nonfinancial Considerations in Eco-Innovation Decisions: The Role of Family Ownership and Reputation Concerns

Societal pressures for greater sustainability can encourage firms to target part of their innovation activities at ecological initiatives (i.e., eco-innovation). Yet, depending on their value function, firms can respond differently to such pressures and exhibit variance in their eco-innovation activities. In this paper, we investigate the idea that a firm’s ownership structure may play a significant role in determining its engagement in eco-innovation. Specifically, we propose that ownership by family blockholders increases the value attached to the company’s reputation and that this, in turn, stimulates higher levels of eco-innovation. In other words, we model the company reputation motive as a key mediator in the relationship between family ownership and firm-level eco-innovation. To account for family firm heterogeneity, we also model the moderating role of owners’ intention to pass the business on to the next family generation (transgenerational intentions) and of the extent to which these owners reside in the firm’s local community (local embeddedness). As theoretical backdrop, our study builds on institutional theory and the mixed gamble logic. To test our hypotheses, we use a large sample of German firms and nonlinear moderated mediation regression analysis. Results reveal that family ownership is positively related to the introduction of eco-innovations by firms, in part because of the stronger emphasis being placed on the company’s reputation. We find that this effect is strongest when the owning-family has transgenerational intentions. As such, this study advances our understanding of firm-level drivers of eco-innovation. In view of the prevalence of family-owned firms and the mounting importance of ecological sustainability, it is valuable to extend knowledge on the contingent and indirect effect of family ownership on eco-innovation.     

Interorganisational project dynamics: A longitudinal study of perceptual distance and client-contractor collaborative relationships

Despite the importance of good collaborative relationships in interorganisational projects, clients and contractors often develop adversarial relationships due to perceptual distance about key project issues. In this case study research, we investigated how perceptual distance emerges and changes over time, and how the collaborative relationship between client and contractor develops alongside these dynamics. In this exploration, we built upon agency theory and stewardship theory as complementary perspectives for understanding client-contractor collaborative relationships. We gathered quantitative and qualitative data in two projects, conducting three assessments in about one year. We found that perceptual distance increased and decreased over time, and that a reduction was typically associated with the collaborative relationship being characterized by stewardship rather than agency. These findings suggest that a regular assessment and evaluation of partners’ perceptions of critical project issues is warranted to timely detect and counteract perceptual distance. Moreover, partners would best adopt a stewardship orientation to reduce perceptual distance, although this may take considerable effort given the distributive nature of many pre-project negotiations.     

Missing the Popular Vote: Pitfalls in US Democracy and Reform Proposals

Intereconomics - Only a few years ago, it was a widespread belief that globalisation would trigger processes of democratisation worldwide. However, even old and established democracies such as the...     

Wie die Materialengpässe den Arbeitsmarkt treffen

Wirtschaftsdienst - Although industrial production in Germany picked up again significantly with the recovery from the Corona crisis, supply bottlenecks for raw materials and intermediate products...     

The Credit Default Swap market contagion during recent crises: international evidence

Review of Quantitative Finance and Accounting - We test the hypothesis that underwriters set higher gross spreads and deeper offer price discounts in seasoned equity offers of firms exhibiting weak...     

What Drives Fraud in a Credence Goods Market? – Evidence from a Field Study

This paper investigates the impact of competition on an expert firm's incentive to defraud its customers in a credence goods market. Controlling for the competence of car repair shops, their financial situation, and reputational concerns, we use and complement the data set from a nationwide field study conducted by the German Automobile Association that regularly checks the reliability of garages in Germany. We find that more intense competition lowers a firm's incentive to defraud its customers.     

Contagion of network products in small-world networks

We formulate a model in which agents embedded in an exogenous social network decide whether to adopt a new network product or not. In the theoretical part of the paper, we characterize the stochastically stable equilibria for complete networks and cycles. For an arbitrary network structure, we develop a novel graph decomposition method to characterize the set of recurrent communication states, which is a superset of stochastically stable equilibria of the adoption game presented in our model. In the simulation part, we study the contagion process of a network product in small-world networks that systematically represent social networks. We simulate a generalization of the Morris (Rev Econ Stud 67(1):57–78, 2000) Contagion model that can explain the chasm between early adopters and early majority. Our numerical analysis shows that the failure of a new network product is less likely in a highly cliquish network. In addition, the contagion process reaches to steady state faster in random networks than in highly cliquish networks. It turns out that marketers should work with mixed marketing strategies, which will result in a full contagion of a network product and faster contagion rates with a higher probability.

     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.     

The impact of traffic sign deficit on road traffic accidents in Nigeria

This study assesses the impact of traffic sign deficit on road traffic accidents in Nigeria. The participants were 720 commercial vehicle drivers. While simple random sampling was used to select 6 out of 137 federal highways, stratified random sampling was used to select six categories of commercial vehicle drivers. The study used qual-dominant mixed methods approach comprising key informant interviews; group interviews; field observation; policy appraisal and secondary literature on traffic signs. Result shows that the failure of government to provide and maintain traffic signs in order to guide road users through the numerous accident black spots on the highways is the major cause of road accidents in Nigeria. The study argues that provision and maintenance of traffic signs present opportunity to promoting safety on the highways and achieving the sustainable development goals.