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Increasingly, manufacturers and service providers face the challenge of improving the environmental performance of their products. A number of studies have shown the importance of environmental goals and measures for successful environmental design efforts in firms. This paper provides a framework of environmental goals or benchmarks and examines Sony Corporation as a case study of improving the environmental performance of products. Specific examples of Sony's targets for improvement are provided along with examples of initiatives for their achievement. In particular, Sony's product assessment check sheet is introduced as a simple yet effective tool for identifying areas for environmental improvement, as well as for measuring and promoting improvement efforts in alignment with the organization's longer‐term environmental goals.

When people buy color TVs, there is one color they really look out for – green. Or so Sony found out in the mid‐1990s when a Dutch consumer magazine gave one of its models a poor environmental rating. Market share fell by 11.5 percent while that of competitors’ TVs which received good ratings increased by 57 and 100 percent. Sony’s response was an environmental policy using internal and external benchmarking to keep ahead of consumer demands and legal requirements.

Financial analysts' forecasts serve as a proxy for market earnings expectations, and research provides mixed evidence of the relation between financial analysts' expertise and forecast accuracy. The judgment and decision-making (J/DM) literature suggests that those with more expertise will not perform better when tasks exhibit either extremely high or extremely low complexity. Expertise is expected to contribute to superior performance for tasks between these two extremes. Using archival data, this research examines the effect of analysts' expertise on forecasting performance by taking into consideration the forecasting task's complexity. Results indicate that expertise is not an explanatory factor for forecast accuracy when the forecasting task's complexity is extremely high or low. However, when task complexity falls between these two extremes, expertise is a significant explanatory variable of forecast accuracy. Both results are consistent with our expectations.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.