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Recognizing the growing role of green sourcing in a supply chain ecosystem, this paper identifies the most common business practices that make green sourcing more successful and then examines the ramifications of green sourcing practices from cost, ecological and cultural perspectives based on cross-national surveys of both Korean and US firms.

After conducting the questionnaire surveys in Korea and the US, we analyzed the results by running a series of binary logistics regression, ordinal regression, canonical correlation, discriminant analyses and chi-square tests of independence and cross-tabulation. These statistical data analyses were also used to test a number of hypotheses and validate the proposed theories.

Analyses of these results revealed significant differences in green sourcing practices between Korean and US firms in that US firms tended to make more substantial commitments to green sourcing than Korean firms. For instance, Korean firms viewed the supplier’s advances in providing eco-friendly packages and goods as the most important attribute for their green supplier selection. In contrast, the US firms prioritized the supplier’s capability to handle hazardous waste disposal and compliance with federal and state environmental regulations in their green supplier selection.

This paper is one of a few studies that expanded the research scope from cross-national and/or cultural perspectives and empirically identified idiosyncrasies unique to the national origin of buying firms that explored green-sourcing initiatives, which aim to reduce the carbon footprints of supply chain activities and minimize unnecessary waste. This paper is also one of the first studies to build a theoretical foundation for worldwide green sourcing practices predicated on institutional and Edgar Schein theories.

There is an ongoing challenge to map the efficacy of e-retailing strategies in building both value co-creation opportunities for online customers and customer value for companies. Based on the service-dominant (S-D) logic, an integrative model is provided that connects the impact of convenience and personalisation strategies (CPSs) on an e-retailer's performance – by offering co-creation opportunities and customer engagement.

The survey instrument is validated and the model is tested with data from active online customers using a novel methodology that blends artificial neural network (ANN) analysis with partial least squares (PLS) in both the measurement model and the path analysis.

The findings robustly support the model and yield evidence of the contribution of CPSs in effective value propositions, the interface between the S-D logic and customer engagement, and the direct effect of customer engagement on tangible forms of value for companies.

This study is the first scholarly effort to provide a comprehensive understanding of how and why CPSs can maximise customer value for the e-retailer, while simultaneously testing the customer value/engagement interface with a new blended ANN-PLS method.

This paper aims to delineate the nature of the costs associated with the diffusion of brand posts. Since cost is an essential component of customer lifetime value, this research also aims to identify factors that impact consumer engagement (CE) with brand posts.

This study conceptualize marginal cost of CE as the ratio of a unit change in cost for a unit change in CE – this ratio is conceptualized for a paid brand post compared to an organic brand post. The authors present a theoretically grounded simulation method that analyzes the relative impact of several factors that influence CE with brand posts. By using an agent-based simulation model, the method presented in this paper helps explain the relative impact of four factors on CE with brand posts on social media.

The authors explain four factors that influence the diffusion of CE with a brand post – promotion-related (i.e. whether it is paid vs organic), network-related, user-related and active periods. The authors also show that the effectiveness of paid posts vs organic posts attributed to a better audience assembled by the seeding algorithms dissipates after the initial stages of diffusion. These findings indicate that paid posts are effective vs organic posts in large part due to higher exposure than due to the efficiency of the algorithms to assemble nodes that are likely to engage with the post.

An agent-based model details the impact of several factors that influence the effectiveness of paid and organic posts and presents methods to analyze the impact of these factors that have implications for theory.

The authors address the difficulty in ascertaining the effectiveness of paid posts by proposing a metric – marginal cost of engagement, defined as the incremental cost incurred by the marketer in earning one additional unit of CE. Since the costs incurred on paid and organic posts differ only on variable components, the marginal cost of engagement presents a way to benchmark paid posts against organic posts, which is very useful for managers in ascertaining the amount to spend on paid posts on social media.

There is little prior research on the costs involved in the diffusion of brand posts on social media. Identifying specific factors that impact costs is valuable for theory and practice.