Menon Business Economics (Norway)

Abstract Energy generated by land-based wind power is expected to play a crucial role in the decarbonisation of the economy. However, with the looming biodiversity and nature crises, spatial allocation of wind power can no longer be considered solely a trade-off against local disamenity costs. Emphasis should also be put on wider environmental impacts, especially if these challenge the sustainability of the renewable energy transition. We suggest a modelling system for selecting among a pool of potential wind power plants (WPPs) by combining an energy system model with a GIS analysis of WPP sites and surrounding viewscapes. The modelling approach integrates monetised local disamenity and carbon sequestration costs and places constraints on areas of importance for wilderness and biodiversity (W&B). Simulating scenarios for the Norwegian energy system towards 2050, we find that the southern part of Norway is the most favourable region for wind power siting when only the energy system surplus is considered. However, when local disamenity costs (and to a lesser extent carbon costs) and W&B constraints are added successively to the scenarios, it becomes increasingly beneficial to site WPPs in the northern part of Norway. We find that the W&B constraints have the largest impact on the spatial distribution of WPPs, while the monetised costs of satisfying these constraints are relatively small. Overall, our results show that there is a trade-off between local disamenities and loss of W&B. Siting wind power plants outside the visual proximity of households has a negative impact on W&B.

Stated preference surveys are increasingly conducted online using internet panel samples, where a fast-growing share of respondents answer on smartphones. These panel members range from novices to “professionals” in terms of previous survey experience. Little is known about the potential effects of smartphone responding and survey experience on the data quality of stated preference surveys. This paper uses a discrete choice experiment dataset on the Norwegian population’s willingness to pay to plant climate forests to explore how these two factors affect data quality. These data by type of response device, gathered using a probability-based internet panel, were combined with a unique dataset obtained from the survey company on respondents’ actual experience answering surveys on different types of devices. Our results show that differences in elicited preferences between smartphone and computer respondents are not caused by the device used, suggesting that initial concerns about smartphone responses may be exaggerated. Furthermore, more experience is associated with an increasing scale parameter (indicating lower error variance), but at a decreasing rate; and a higher propensity to choose the status quo (indicating possible simplifying strategies employed by respondents). Combined this suggest some optimal level of experience that is neither too high nor too low. We discuss the implications of our results for stated preference research and provide a few avenues for future research.

Invasive alien species (IAS) are identified as a major threat to biodiversity and ecosystem services. While early detection and control programs to avoid establishments of new alien species can be very cost-effective, control costs for well-established species can be enormous. Many of these well-established species constitute severe or high ecological impact and are thus likely to be included in control programs. However, due to limited funds, we need to prioritize which species to control according to the gains in ecological status and human well-being compared to the costs. Benefit-Cost Analysis (BCA) provides such a tool but has been hampered by the difficulties in assessing the overall social benefits on the same monetary scale as the control costs. In order to overcome this obstacle, we combine a non-monetary benefit assessment tool with the ecosystem service framework to create a benefit assessment in line with the welfare economic underpinnings of BCA. Our simplified BCA prioritization tool enables us to conduct rapid and cheap appraisals of large numbers of invasive species that the Norwegian Biodiversity Information Centre has found to cause negative ecological impacts. We demonstrate this application on 30 well-established invasive alien vascular plant species in Norway. Social benefits are calculated and aggregated on a benefit point scale for six impact categories: four types of ecosystem services (supporting, provisioning, regulating and cultural), human health and infrastructure impacts. Total benefit points are then compared to the total control costs of programs aiming at eradicating individual IAS across Norway or in selected vulnerable ecosystems. Although there are uncertainties with regards to IAS population size, benefits assessment and control program effectiveness and costs; our simplified BCA tool identified six species associated with robust low cost-benefit ratios in terms of control costs (in million USD) per benefit point. As a large share of public funds for eradication of IAS is currently spent on control programs for other plant species, we recommend that the environmental authorities at all levels use our BCA prioritization tool to increase the social benefits of their limited IAS control budgets. In order to maximize the net social benefits of IAS control programs, environmental valuation studies of their ecosystem service benefits are needed.

Sensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good. Establishing significant scope sensitivity has been an important check of validity and a point of contention for decades in stated preference research, primarily in contingent valuation. Recently, researchers have begun to differentiate between statistical and economic significance. This paper contributes to this line of research by studying the significance of scope effects in discrete choice experiments (DCEs) using the scope elasticity of willingness to pay concept. We first formalize scope elasticity in a DCE context and relate it to economic significance. Next, we review a selection of DCE studies from the environmental valuation literature and derive their implied scope elasticity estimates. We find that scope sensitivity analysis as validity diagnostics is uncommon in the DCE literature and many studies assume unitary elastic scope sensitivity by employing a restrictive functional form in estimation. When more flexible specifications are employed, the tendency is towards inelastic scope sensitivity. Then, we apply the scope elasticity concept to primary DCE data on people’s preferences for expanding the production of renewable energy in Norway. We find that the estimated scope elasticities vary between 0.13 and 0.58, depending on the attribute analyzed, model specification, geographic subsample, and the unit of measurement for a key attribute. While there is no strict and universally applicable benchmark for determining whether scope effects are economically significant, we deem these estimates to be of an adequate and plausible order of magnitude. Implications of the results for future DCE research are provided.

Despite a large stated-preference (SP) literature on wind power externalities, few SP studies employ a case-control approach to examine whether people's acceptance of new wind power developments and renewable energy initiatives increases or decreases with exposure. Furthermore, the existing studies are inconclusive on this issue. In a case-control discrete choice experiment, we measure the level of acceptance in terms of people's willingness-to-accept (WTA) for having future land-based wind power developments in Norway; comparing exposed and non-exposed people's WTA. We find that exposure lowers acceptance. Furthermore, exposed people are also unwilling to pay as much to increase general domestic renewable energy production (from all sources) as non-exposed people, and thus have lower acceptance for such renewable energy policy initiatives. After testing for type of exposure, we argue that the inconclusiveness in the literature of how exposure affects acceptance of wind power developments could be due to the fact that impacts considered differ somewhat across studies.

The perception of the CEO as the strategic leader in an organization that dominated much of the leadership research in past decades as well as the more recent focus on top management teams as sources of strategic leadership runs contrary to the often observed fact that organizations have numerous leaders at all levels, not merely in the upper echelons. More importantly, it ignores the existence of leadership networks permeating formal organizational structures. These networks with dynamically shifting leader–follower roles, as dictated by the situational demands and individual capabilities, are a means of achieving competitive advantage and building healthy organizations in complex and turbulent environments. This chapter introduces different forms of strategic leadership networks—which we call generic forms of strategic leadership. Their key features will be described.

The charisma of strategic leaders can be an important means for mobilizing human and social capital of an organization irrespective of the form of strategic leadership. By communicating a shared vision and a sense of purpose among the organizational members, strategic leaders can motivate followers in ways that are often stronger than formal control systems, performance metrics, and financial rewards. Common goals and values articulated by charismatic leaders and the mutual dependence they instill can create the basis for building strategic leadership networks across units and organizational levels. However, there is a dark side to charisma, where it often leads to managerial hubris and excessive attention to exploration without a balancing concern for monitoring and controlling organizational costs while operating in complex and turbulent environments.

Purpose The Norwegian travel industry faces decline in important international tourism segments and needs an industry wide and future‐oriented strategy to face these challenges. Accordingly, a common understanding of future drivers and different scenarios for the industry is needed. The paper aims to discuss these issues. Design/methodology/approach Using the process of scenario analysis and drawing upon the involvement of the tourism industry, this paper describes the method, drivers, scenarios, and implications. Findings The research identified six important drivers with predictable outcomes: uneven global economic development, digitalization, climate change, consumer demand – return on time, centralization, and demography. The Norwegian economy and Norwegian politics were the two drivers that stood out as the most significant for the tourism industry, with a very uncertain outcome, and constituted the two axes of the scenarios. This resulted in four scenarios: Money Rules, The Urban Diamond, Opportunities for All, and Master Plan. Practical implications The four scenarios represent different economic value of international tourism in Norway. The Opportunities for All and Master Plan scenarios represent the greatest economic value for Norwegian tourism. They indicate great opportunities for tourism to become the “new oil” in Norway if the oil economy declines. The two scenarios differ with respect to the degree of governance control vs market liberalization. The scenarios will be used to identify implications and risks for different parts of the tourism industry, and to further explore how governance control and market liberalization may be combined. Originality/value The research identified six drivers which are significant for the Norwegian tourism industry. This resulted in four scenarios which are used to identify implications and risks for different parts of the industry.