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In the last two decades, the dependence of Taiwan’s manufacturing production on imported intermediate inputs has steadily risen. Meanwhile, the market share of imported consumable manufacture products has also increased. The steady rise of both import shares may not be explained by price fact or since the relative import prices have shown no decreasing trend. The scenario of constantly buying more imported goods when they are not cheaper can be treated as a preference change in favor of imported goods, which may be caused by the popularity of outsourcing, increasing product varieties and persistent trade barriers, as literatures indicated. Traditional macroeconomic models primarily consider the price mechanism in their import demand estimates, with no concern for changes in import preferences. Neglecting changing import preferences in a rapid globalization environment may yield biased empirical results. In this article, we incorporate the import preference factor into a single-country Computable General Equilibrium (CGE) model and use it firstly to quantify the scale of preferences change and then to test how the preferences change affects the effects of trade policy. The empirical results with and without the concern of import preferences change are compared to yield the scale of bias caused by neglecting the change.

Using a discrete choice experiment (DCE), this study aims to better understand the job preference of postgraduate students studying at the Kwame Nkrumah University of Science and Technology-Institute of Distance Learning, Ghana and also rank the attributes of a job they deem important.

The research adopted a positivist epistemological design contextualised within a deductive approach and case study strategy. Primary survey data was collected from a stratified random sample of 128 postgraduate students with multi-sectorial career prospects. Sample students were subjected to a DCE in which their stated preferences were collected using closed-ended questionnaires with 28 pairs of hypothetical job profiles. Respondents’ preferences from the DCE data were then modelled using the conditional logit.

The research reveals that: salary in the range GHC 2,800.00 to GHC 3,400.00 ($1 = GHS 5.3); supportive management; very challenging jobs; and jobs located in the city were the top attributes that were significant and had the most impact in increasing the utility of selecting a particular job. Interestingly, jobs with no extra hours workload were not significant hence, had a negative impact upon student preferences.

This novel research is the first to use a DCE to better elicit preference and trade-offs of postgraduate students in a developing country towards varying job characteristics that have an impact on their future employment decisions. Knowledge advancements made provide invaluable insight to employers and policymakers on the key criteria that should be implemented to retain the best candidate.

The purpose of this paper is to provide insights for flower retailers, horticultural practitioners and marketing managers into the prioritisation of cut flower attributes by German residents.

Applying a best–worst scaling approach, this analysis identified the relative ranking of importance amongst product attributes relevant to German consumers when buying fresh cut flowers. A latent class analysis determined four flower consumer segments for further study. The study builds on a sample of 978 consumers and is consistent with the most recent German census in terms of age, gender, income and federal state.

The best-worst analysis showed that intrinsic flower attributes, in particular appearance, freshness and scent were found to be more important to German consumers than the extrinsic attributes studied, namely, price, country of origin and a certification indicating fair trade. The latent class analysis determined four consumer segments that desire either budget, luxury or ethical flowers or more information about flowers. For all identified consumer segments, appearance was the attribute of greatest importance. The segments that desired luxury or ethical flowers, as well as the segment that desires more information were interested in appearance, but also had relatively large shares of preferences dedicated to flower freshness guarantees. The preference for freshness guarantees in addition to appearance may be interpreted jointly as a desire for not only beautiful and aesthetically pleasing flowers, but for sustained beauty.

Internationally, the study fills a research gap by exploring consumer’s relative preference for cut flower attributes. In contrast to existing studies on consumer preferences for flowers in Germany, the present study builds on a sample that was targeted in terms of age, gender, net household income and federal state to the most recent German census.

This paper investigates the impact of sustainability information disclosure on consumers' choice of order-to-delivery lead-time in relation to consumers' sustainability concern.

Based on two choice experiments with participants from the Netherlands (n = 348) and the United Kingdom (n = 1,387), the impact of sustainability information disclosure was examined in connection with consumers' concerns for environmental and social sustainability. Information on environmental impact (carbon emission) and social impact (warehouse workers and drivers' well-being) was considered and compared.

Disclosing sustainability impact information significantly increased consumers' preference and choice for longer delivery times, with equivalent effects for environmental and social impact information. Consumers' relevant (environmental or social) sustainability concern as personality traits enhanced effects on preferences, as did priming of environmental concern.

Future research may consider differences between product categories or e-commerce companies' reputation in sustainability activities.

The findings provide opportunities for online retailers to influence consumer choice of delivery time, especially through disclosing environmental and/or social sustainability information.

This study fills a gap in the literature on sustainability information disclosure to actively steer consumer choice of delivery time, particularly regarding the effect of social sustainability impact information in comparison to its environmental counterpart.

The purpose of this paper is to show that the environmental income drives economic growth of a large open country.

The authors detect that the relative environmental income has double effect of “conspicuous consumption” on the international renewable resource stock changes when a new social norm shapes to environmental-friendly behaviors by using normal macroeconomic approaches.

Every unit of extra demand for renewable resource consumption increases the net premium of domestic capital asset. Even if the technology spillovers are inefficient to the substitution of capital to labor force in a real business cycle, the relative income with scale effect increases drives savings to investment. In this case, the renewable resource consumption promotes both the reproduction to a higher level and saving the potential cost of environmental improvement. Even if without scale effects, the loss of technology inefficient can be compensated by net positive consumption externality for economic growth in a sustainable manner.

It implies how to earn the environment income determines the future pathway of China’s rural conversion to the era of eco-urbanization.

We test the tax incidence to demonstrate an experimental taxation for environmental improvement ultimately burdens on international consumption side.

The purpose of this paper is to introduce the main measures of inconsistency in the context of intertemporal choice and to identify the relationships between them (more specifically, the measures by Prelec, Takahashi and Rohde). In effect, Thaler (1981), awarded the Nobel Prize in Economics 2017, argued that when a preference must be expressed between two reward options, some people may reverse their original preference when a significant delay is introduced before the reward is to be received. This anomaly is known as inconsistency in intertemporal choice.

After a revision of the existing literature and by using the methods from mathematical calculus, the authors have derived the logical relationships between the measures presented in this paper.

The main contribution of this paper is the proposal of a novel parameter, the so-defined ratio of two instantaneous discount rates, which the authors call the instantaneous variation rate, which allows relating some other measures of inconsistency, namely the measures described by Prelec and Rohde. A limitation of this paper is the unavailability of empirical information about the inconsistency measures needed to substantiate the theoretical findings. Indeed, this paper has social implications because recent behavioral and neuroeconomic studies have shown the existence of preference reversal or time inconsistency in other areas. The authors’ models can be implemented in these fields in order to better analyze the situations of inconsistency.

The originality of this paper lies in the authors’ aim to bring some order to the proposed measures of inconsistency which have arisen as a result of the different approaches adopted.

Applying the institutional logics perspective to applicant attraction, this study investigates the level of uniformity among preferences for consulting job attributes associated with the institutional logics of the corporation, the profession and the family, and tests for the influence of anticipatory socialization differences.

The study uses a discrete choice experiment with 232 business students. A hierarchical Bayes approach to conjoint analysis uncovers part-worth heterogeneity and allows for subsequent cluster and regression analysis of the choice data.

The findings identify a dominant job-oriented preference type and a minor career-oriented preference type. Anticipatory socialization through personal prior work experience and the occupation of friends decreases adherence to the logic of profession and increases the relevance of the family logic. The parents' occupation has only a minimal influence on preferences.

The study provides attribute-based recommendations on how professional service firms can effectively address the complex expectations of potential applicants in their job ads for an entry position and underlines the role of intra-generational reference groups as important anticipatory socializers.

By testing individual socialization effects at the pre-hire stage and beyond the organizational level, the study fills a void in both the recruitment and the institutional literature.

The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

A flexible decision technology called the Graph Model for Conflict Resolution (GMCR) is applied to a generic aquaculture conflict to illustrate how GMCR can be used to systematically investigate a wide range of conflicts arising in aquaculture in order to obtain meaningful strategic insights and thereby assist in making informed decisions in aquaculture development. To emphasize the importance of being able to resolve aquaculture controversies, a review of the global economic impacts of the aquaculture industry is provided and the key stakeholders who may be involved in aquaculture disputes along with their legitimate interests are identified. The paper aims to discuss these issues.

The GMCR methodology comprises two main stages: modeling and analysis. During the modeling stage, key decision makers (DMs), the options under each DM’s control and each DM’s relative preferences over feasible states are identified based on a thorough background investigation to a given dispute. Within the analysis stage, solution concepts that describe key characteristics of human behavior under conflict are utilized to determine resolutions that could occur when DMs interact under pure competition and cooperatively. Interpretation of the equilibrium results provides meaningful strategic insights for better understanding which strategies a given DM could select as the conflict evolves over time.

The results demonstrate how difficult it can be to balance the interests of different key stakeholders in aquaculture development. In all possible resolutions identified in the generic aquaculture conflict, at least two DMs among First Nations, environmental group and residents (Res) would object to the expansion of aquaculture activities due to the assumption that the government would choose to appease one stakeholder at a time. They also reflect the need for a useful tool box of decision technologies for addressing the vast range of challenges that could arise in the important area of marine economics and management.

The GMCR methodology possesses several unique and key original capabilities in comparison to other conflict analysis models. First, it only requires limited information to calibrate a conflict model. Second, it contains a number of solution concepts that describe how a DM could think and behave under conflict. Third, it furnishes a range of informative output, follow-up analyses and advice for use in real-life decision support. Finally, all of the foregoing advantages of GMCR can be contained within decision support systems that permit practitioners and researchers to readily apply the GMCR methodology to real-life conflicts.

The feasibility and desirability of reverse logistics in market-motivated contexts are examined in China. Interactions between the major barriers, that hinder or prevent the application of reverse logistics in China are analyzed. Management’s key task is to diagnose barriers to the application of reverse logistics that could be crucial to the organization’s future survival. Simultaneity, a value delivery system exists to create value for customers and environments by supplying needed products and services. Value delivery systems are at the heart of every firm and, more than anything else, determine that, whether the firm survives in the marketplace or disappears into bankruptcy or takeover. The processes and model of market-motivated reverse logistics value delivery system are discussed, and the processes content and model are presented. Simultaneity, based on the advantage of the Third Party Reverse Logistics Providers (3PRLs) and Outsourced Service Providers, an integrated evaluation model is built to select 3PRLs by using the integrated decision-making methods. Reflecting the comprehensive information requirement, the Analytic Hierarchy Process and entropy approaches are applied to calculate the objective weights. A new kind of relative similarity degree is established by combining the Euclidean distance with the grey correlation degree. An example demonstrates the model’s efficiency.