The formation of habit and word-of-mouth intention of over-the-top platforms

The current study examines how video content on over-the-top (OTT) platforms and the enjoyment from watching them form habits and word-of-mouth (WOM) intentions. We propose a research model that integrates elements from the Self-Determination Theory (SDT) and the concept of “habit loop” from the Interest-Driven Creator (IDC) theory. The model was analyzed using PLS-SEM on 302 responses from OTT users. The study elucidates how video content availability helps in habit formation indirectly through perceived enjoyment. The results also demonstrated that the WOM of OTT platforms is explained by perceived enjoyment, affective commitment, and the habit of using the OTT platforms. The study highlights that habit is a significant predictor of affective commitment and WOM intention of hedonic apps. This is the first study to illustrate how video content availability affects users’ enjoyment, habitual use, and WOM intentions. Habit as a significant predictor of affective commitment and WOM intention of hedonic apps, like OTT platforms, is unprecedented.     

Circular business model implementation: A capability development case study from the manufacturing industry

Circular business models (CBMs) have huge potential to deliver economic, social, and environmental benefits, but CBMs have yet to be implemented widely in industrial settings. One reason is that they are often presented as one-size-fits-all solutions, but this is misplaced because product-specific criteria and company capabilities determine the correct choice and implementation of CBMs. Therefore, the purpose of this paper is to investigate how CBM selection and capability development facilitates the implementation of CBMs. For this purpose, we have adopted a qualitative research approach and undertaken 25 explorative interviews in three large Swedish manufacturing companies. In this paper, a CBM implementation framework consisting of two parts has been developed. The first part addresses the choice of the appropriate CBM based on tactical configurations. The second part provides a capability development path by explicating underlying routines that need to be progressively developed in order to move smoothly to more advanced CBMs.     

Quantifying landscape externalities of renewable energy development: Implications of attribute cut-offs in choice experiments

Renewable energy is worldwide seen as a key element necessary to address climate change. However, finding socially acceptable locations for renewable energy facilities and the accompanying infrastructure increasingly often faces fierce opposition. This paper quantifies the landscape externalities of renewable energies employing a choice experiment. In addition, it is investigated how accounting for non-compensatory choice behavior, i.e. attribute cut-offs, affects welfare measures and subsequently policy recommendations. The empirical application is Germany where we conducted a nationwide survey on the development of renewable energies. We first show that cut-off elicitation questions prior to the choice experiment at least partially influence preferences. We further find that most participants state cut-off levels for attributes. Many are, however, at the same time willing to violate the self-imposed thresholds when choosing among the alternatives. To account for this effect, stated cut-offs are incorporated into a mixed logit model following the soft cut-off approach. Model results indicate substantial taste heterogeneity in preferences and in the use of cutoffs. Also, welfare estimates are substantially affected. We conclude that welfare changes from renewable energy development could be strongly underestimated when cut-offs are ignored.     

An Investigation into Restaurant Attributes: A Basis for a Typology

This article has the aim of presenting the basis for a new, clearer classification of restaurant attributes. The research followed an interpretive approach with a systematic review of the literature, compared and contrasted with the findings of six focus group interviews. A new model was devised with seven categories of restaurant attributes. This article presents a model that needs to be tested. Also, follow-up articles with more detail about the attributes under each category will be presented. This article organizes the disparate literature on restaurant attributes and looks into the relationship between attributes, particularly its influence on perceived consumer value.     

Reviewing the DATAS of aviation research data: Diversity,availability, tractability,applicability, and sources

The field of aviation research is entering the era of big data. While data-driven advancements in aviation have clearly brought about applicable models and results with immediate implications, we argue that the influx of aviation data should be better characterized and documented to enable more efficient and standardized usage. To this end, we examine 200 well-cited research articles from sub-disciplines ranging from revenue management to air traffic control published on or after 2010 in order to analyze the diversity, availability, tractability, applicability, and sources (DATAS) of data utilized in aviation research. We find high levels of data diversity within aviation research, with 16 data categories ranging from air traffic flow management-type data to data from distributed sensors in line with the Internet-of-Things (IoT) paradigm. We identified a dominance of proprietary, non-public data in aviation research, with 68% of the 200 research articles utilizing solely proprietary data in deriving their results, and a further 8% utilizing a mixture of proprietary and publicly available data. The pervasiveness of proprietary data has implications on reproducibility and extending research results. We also highlight the increasing tractability of the data by surveying the computational power required to process the data sets, and present vignettes of applications and results that stem from these data-driven studies. Finally, we propose several recommendations regarding standardizing data source nomenclature as well as increasing the availability of and usage of publicly available data.     

An application of two-stage quantile regression to insurance ratemaking

Two-part models based on generalized linear models are widely used in insurance rate-making for predicting the expected loss. This paper explores an alternative method based on quantile regression which provides more information about the loss distribution and can be also used for insurance underwriting. Quantile regression allows estimating the aggregate claim cost quantiles of a policy given a number of covariates. To do so, a first stage is required, which involves fitting a logistic regression to estimate, for every policy, the probability of submitting at least one claim. The proposed methodology is illustrated using a portfolio of car insurance policies. This application shows that the results of the quantile regression are highly dependent on the claim probability estimates. The paper also examines an application of quantile regression to premium safety loading calculation, the so-called Quantile Premium Principle (QPP). We propose a premium calculation based on quantile regression which inherits the good properties of the quantiles. Using the same insurance portfolio data-set, we find that the QPP captures the riskiness of the policies better than the expected value premium principle.     

Prioritising alternatives for sustainable end-of-life vehicle disassembly in China using AHP methodology

The projection on Chinese increasing end-of-life vehicle (ELV) volumes indicates that the volume in 2020 will be about threefold that in 2015. The issue of scrapping vehicle upsurge relative to capacity crunches and environmental impacts perplexes Chinese dismantlers and it is intractable and urgent to choose an appropriate dismantling mode. The purpose of this study is to prioritise four potential dismantling modes and provide decision-making reference for dismantlers with a view to such criteria as environmentally sustainable considering constraints involving economy, technique, ecology and flexibility over changing condition. The conducted evaluation by the analytical hierarchy process (AHP) methodology takes sensitive and problematic aspects into account through questionnaires. The whole evaluation process supported by expert preferences, provides a simple and intuitive knowledge to construct arguments for ELV decision-making process. Results show that disassembly line involves the highest global weight of 0.363 and is concluded to be the best compromised ecological alternative.     

Using methods of Multi-Criteria Decision Making to provide decision support concerning local bioenergy projects

The public sector plays an important role in the German “Energiewende”. Besides energy management in municipal properties the local government can also support the switch to renewable energy sources through a change in energy supply structures within in their region. Methods of Multi-Criteria Decision Making (MCDM) from Operations Research are helpful regarding that challenge, as they are able to assess the sustainability of local energy concepts, since they not only offer stakeholders the opportunity to participate, but also consider multiple conflicting criteria. In that way, the acceptance of local energy projects and the participation of stakeholders in the decision process are supported. The case study presented in this paper illustrates the results of a MCDM process employed to identify a sustainable bioenergy concept in a rural village in Lower Saxony, Germany. Our analysis revealed not only the opportunities and challenges associated with executing an MCDM process to support the realization of local bioenergy projects, but also discusses potential limitations of the methods.     

An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

With the expansion of urbanization caused by the growth of population and industrial activities, the urban/city and suburban areas are facing a variety of environmental threats. Although more research and urban policy has advocated and practiced the development of green infrastructure (GI) to support urban sustainable environment, the evaluation framework for the development of GI for promoting environmental sustainability is still insufficient. Moreover, the Analytic Hierarchy Process (AHP) commonly applied in published literature, makes an unrealistic assumption of independent relationships among dimensions/criteria in decision making for satisfying the real-world problem. Therefore, the purpose of this study is to construct the evaluation framework, including four dimensions and related ten criteria, using a new hybrid-modified multiple attribute decision-making (MADM) model for developing and improving the GI for promoting environmental sustainability. This MADM model is combined with three different methodologies of MADM, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for constructing the influential network relation map (INRM) to explore the complex influential inter-relationships and DEMATEL based on Analytic Network Process (DANP) for determining the influential weights with the VIse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating and presenting improvement strategies for six different GIs. The empirical study indicates that DEMATEL and DANP Results suggest that decision-makers should pay more attention to the improvement of Design (D₄) and Materials (D₂) in terms of dimensions when utilizing the GI to promote environmental sustainability. Because these dimensions are enhanced, Species (D₁) and Energy (D₃) will be improved in synchronization. From the perspective of criteria, five are key core criteria and need to be focused on first: increasing the green coverage rate (B₉), utilizing sustainable materials (B₄), using ecological engineering (B₈), shaping species biodiversity (B₁), and reducing energy consumption (B₅). Modified VIKOR reveals that “grass swales” are a comparatively better choice among six GIs for promoting environmental sustainability toward achieving the aspiration level. Therefore, this MADM model is beneficial to provide a more convincing assessment framework and improvement strategies for the development of GI for promoting environmental sustainability. As a result, these modified MADM models can be shown more conveniently and reasonably than traditional methods such as traditional AHP or ANP method.     

Low-carbon decision-making model of online shopping supply chain considering the O2O model

A demand function of online shopping supply chain based on online-to-offline (O2O) fusion degree is proposed by considering the low-carbon awareness of online shoppers in view of the low-carbon decision making of supply chain in combination with the O2O operation background. On this basis, a low-carbon decision-making model based on online stores and their suppliers is established, and the application of the model is analyzed. Results show that the promotion of low-carbon operation is efficient when the consistency of online and offline operations of online stores and their suppliers is high. In addition, the decision making considering the cost of carbon information release is highly conducive to improving the low-carbon awareness of online shoppers if the low-carbon level of online shopping goods is lower than the low-carbon standard. Accordingly, the low-carbon operation of online shopping supply chain will be promoted.