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.     

Technologies in caregiving: professionals’ strategies for engaging with new technology

This article explores the adoption of new technology in organisations that provide senior citizen care. Inspired by Niklas Luhmann’s systems theory, we study how technology reduces complexity by identifying client needs and ensuring predictability in service delivery. However, how technologies are adopted in practice is not determined by technology since it is also structured by care-workers' continuous decision-making. Against this backdrop, we explore how technologies alter the conditions for decision-making in two settings of elderly care, and we describe how care workers seek to adapt technologies to their practical needs as well as conception of care ethics. Developing a systems theory approach, the article eschews a priori assumptions of technological constraint on care-workers’ professional autonomy, offering a more open-ended exploration of diversified strategies for coping with new technology. Our case studies show that employees develop diversified strategies for technology adoption, including both non-usage, heated resistance, excessive embrace, and creative adaption.     

Coping with coopetition—Facing dilemmas in cooperation for sustainable development: The case of the Dutch smart grid industry

This paper is amongst the first to examine coopetition strategy for sustainable development at the network level. Companies who want to successfully implement complex innovative technologies that support sustainable development need to collaborate with other actors of the innovation ecosystem, including their competitors, so that they can develop standards, interoperable products, pool knowledge, and resources and bundle forces to compete against other technologies. Collaboration with competitors brings benefits, but also many risks. We investigated how firms cope with these risks when establishing an innovation ecosystem to implement a new technology in society. We conducted research in the Dutch smart grids sector and explored how these firms minimize inherent risks of coopetition. We found that system‐building actors in the Dutch smart grid field not only minimize inherent risks, but from the start of their collaboration they implement so‐called enablers to prevent these risks upfront.     

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.

     

Measuring lnequality in the Middle East 1990–2016: The World’s Most Unequal Region?

In this paper we combine household surveys, national accounts, income tax data and wealth data in order to estimate income concentration in the Middle East for the period 1990–2016. According to our benchmark series, the Middle East appears to be the most unequal region in the world, with a top decile income share as large as 64 percent, compared to 37 percent in Western Europe, 47 percent in the US and 55 percent in Brazil (see Alvaredo et al. 2018). This is due both to enormous inequality between countries (particularly between oil‐rich and population‐rich countries) and to large inequality within countries (which we probably under‐estimate, given the limited access to proper fiscal data). We stress the importance of increasing transparency on income and wealth in the Middle East, as well as the need to develop mechanisms of regional redistribution and investment.     

Integrated bio-economic models as tools to support land-use decision making: a review of potential and limitations

Bio-economic modelling has become a useful tool for anticipating the outcomes of policies and technologies before their implementation. Advances in mathematical programming have made it possible to build more comprehensive models. In an overview of recent studies about bio-economic models applied to land-use problems in agriculture and forestry, we evaluated how aspects such as uncertainty, multiple objective functions, system dynamics and time have been incorporated into models. We found that single objective models were more frequently applied at the farm level, while multiple objective modelling has been applied to meet concerns at the landscape level. Among the objectives, social aspects are seldom represented in all models, when being compared to economic and environmental aspects. The integration of uncertainty is occasionally a topic, while stochastic approaches are more frequently applied than non-stochastic robust methods. Most multiple-objective models do not integrate uncertainty or sequential decision making. Static approaches continue to be more recurrent than truly dynamic models. Even though integrating multiple aspects may enhance our understanding of a system; it involves a tradeoff between complexity and robustness of the results obtained. Land-use models have to address this balance between complexity and robustness in order to evolve towards robust multiple-objective spatial optimization as a prerequisite to achieve sustainability goals.     

Investor Pessimism and the German Stock Market: Exploring Google Search Queries

We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.