This ebook derives from the 7th Global Brand Conference of The Academy of Marketings Special Interest Group on Brand, Corporate Identity and Reputation, held at Oxford University in 2011. The ...authors explore the challenges brand management faces as customers increasingly demand multisensory and multi-experiential brand interactions. A wide variety of current issues are addressed, from the increasingly important aspect of brand impact to the long-lasting experiences that organizations seek in order to achieve brand success in the global marketplace.
Despite the consensus on the negative country-level implications of corruption, its consequences for firms are less understood. This study examines the effect of bribery on the innovative performance ...of firms in emerging markets as reflected by new product introductions. I argue that bribery may help innovators in these markets to introduce new products by overcoming bureaucratic obstacles, compensating for the lack of kinship or political affiliations, and hedging against political risk. I also propose that the relationship between firm bribery and new product introduction will be negatively moderated (i.e., weakened) by the quality of the formal and informal institutions in place. Employing data from over 6,000 firms in 30 emerging markets and a wide range of empirical tests, my results support these hypotheses. These findings extend transaction costs economics by showing that bureaucratic obstacles and uncertainty can drive firms into illegal cost minimization strategies. Moreover, they augment institutional theory by expounding upon the ways that norms and informal practices moderate the efficiency of firm strategies in emerging markets.
Development of new products often relies on the discovery of novel molecules. While conventional molecular design involves using human expertise to propose, synthesize, and test new molecules, this ...process can be cost and time intensive, limiting the number of molecules that can be reasonably tested. Generative modeling provides an alternative approach to molecular discovery by reformulating molecular design as an inverse design problem. Here, we review the recent advances in the state‐of‐the‐art of generative molecular design and discusses the considerations for integrating these models into real molecular discovery campaigns. We first review the model design choices required to develop and train a generative model including common 1D, 2D, and 3D representations of molecules and typical generative modeling neural network architectures. We then describe different problem statements for molecular discovery applications and explore the benchmarks used to evaluate models based on those problem statements. Finally, we discuss the important factors that play a role in integrating generative models into experimental workflows. Our aim is that this review will equip the reader with the information and context necessary to utilize generative modeling within their domain.
This article is categorized under:
Data Science > Artificial Intelligence/Machine Learning
Generative modeling approaches can be used to discover novel and diverse compounds.
This article suggests that dynamic capabilities can give the firm competitive advantage, but this effect is contingent on the level of dynamism of the firm's external environment. A nonlinear, ...inverse U-shaped moderation is proposed, implying that the relationship between dynamic capabilities and competitive advantage is strongest under intermediate levels of dynamism but comparatively weaker when dynamism is low or high. This proposition is tested using data on alliance management capability and new product development capability, two specific dynamic capabilities widely recognized in prior research. Results based on longitudinal key informant data from 279 firms support the account that these dynamic capabilities are more strongly associated with competitive advantage in moderately dynamic than in stable or highly dynamic environments.
Ocean salinity records the hydrological cycle and its changes, but data scarcity and the large changes in sampling make the reconstructions of long-term salinity changes challenging. Here, we present ...a new observational estimate of changes in ocean salinity since 1960 from the surface to 2000 m. We overcome some of the inconsistencies present in existing salinity reconstructions by using an interpolation technique that uses information on the spatiotemporal covariability of salinity taken from model simulations. The interpolation technique is comprehensively evaluated using recent Argo-dominated observations through subsample tests. The new product strengthens previous findings that ocean surface and subsurface salinity contrasts have increased (i.e., the existing salinity pattern has amplified). We quantify this contrast by assessing the difference between the salinity in regions of high and low salinity averaged over the top 2000 m, a metric we refer to as SC2000. The increase in SC2000 is highly distinguishable from the sampling error and less affected by interannual variability and sampling error than if this metric was computed just for the surface. SC2000 increased by 1.9% ± 0.6% from 1960 to 1990 and by 3.3% ± 0.4% from 1991 to 2017 (5.2% ± 0.4% for 1960–2017), indicating an acceleration of the pattern amplification in recent decades. Combining this estimate with model simulations, we show that the change in SC2000 since 1960 emerges clearly as an anthropogenic signal from the natural variability. Based on the salinity-contrast metrics and model simulations, we find a water cycle amplification of 2.6% ± 4.4% K−1 since 1960, with the larger error than salinity metric mainly being due to model uncertainty.
Retail forecasting: Research and practice Fildes, Robert; Ma, Shaohui; Kolassa, Stephan
International journal of forecasting,
10/2022, Volume:
38, Issue:
4
Journal Article
Peer reviewed
Open access
This paper reviews the research literature on forecasting retail demand. We begin by introducing the forecasting problems that retailers face, from the strategic to the operational, as sales are ...aggregated over products to stores and to the company overall. Aggregated forecasting supports strategic decisions on location. Product-level forecasts usually relate to operational decisions at the store level. The factors that influence demand, and in particular promotional information, add considerable complexity, so that forecasters potentially face the dimensionality problem of too many variables and too little data. The paper goes on to evaluate evidence on comparative forecasting accuracy. Although causal models outperform simple benchmarks, adequate evidence on machine learning methods has not yet accumulated. Methods for forecasting new products are examined separately, with little evidence being found on the effectiveness of the various approaches. The paper concludes by describing company forecasting practices, offering conclusions as to both research gaps and barriers to improved practice.
Entrepreneuring as Emancipation Rindova, Violina; Barry, Daved; Ketchen, David J.
The Academy of Management review,
07/2009, Volume:
34, Issue:
3
Journal Article
Peer reviewed
We define "entrepreneuring" as efforts to bring about new economic, social, institutional, and cultural environments through the actions of an individual or group of individuals. Thus, we view ...entrepreneuring as an emancipatory process with broad change potential. This view foregrounds three aspects of entrepreneuring that merit closer attention in future research -- seeking autonomy, authoring, and making declarations. We highlight the novel directions for entrepreneurship research suggested by our emancipatory perspective and relate it to the special topic forum articles.
Social media platforms can be a promising tool for retailers’ marketing campaigns. Especially for the purpose of new product introductions, social media may facilitate social interaction and online ...word-of-mouth and therefore, may broaden the reach and accelerate the diffusion of information about the new product. The impact of online word-of-mouth communication and social interaction on consumer behavior has been extensively analyzed in previous research. However, little knowledge exists so far on the influence of social media campaigns on new product introductions. Therefore, the goal of this study is to analyze the impact of a social media campaign on the success of a new product introduction by using survey as well as behavioral data. The data stems from an online community related to a social media tryvertising campaign implemented to promote the introduction of new high-end binoculars. The results of a mediation analysis show that campaign-related factors positively influence consumers’ attitude toward the new product, which in turn mediates the positive influence on purchase intention and recommendation behavior. Furthermore, a post-hoc analysis shows the importance of community members’ activity on the success of the new product introduction.
This research identifies a surprising downside to using crowdsourcing to generate new product ideas: participants who do not win an idea generation contest temporarily disengage from the ...contest-hosting brand. When people lose a crowdsourcing contest, the experience of losing negatively affects the participants’ word-of-mouth and short-term purchase behaviors. Reframing the contest as a community activity (e.g., “Join the crowd and help us find a name for our new restaurant”) rather than a competition (e.g., “Compete with the crowd to be the one who names our new restaurant”) is found to positively affect a losing customer's subsequent engagement with the contest-hosting brand. Community framing shifts attention away from losing the contest (i.e., it reduces negative affect) and toward collectively creating a superior outcome (i.e., it increases one's perceived contribution), without changing the nature of the contest itself (i.e., participants continue to submit ideas). Community framing positively affects subsequent participant engagement, but it does not influence the effort the participant invests in the contest or the quality of the idea the participant submits. The evidence consists of lab experiments, field experiments, and a large-scale field study that measured actual purchase behavior.
Based on MOD09GA/MYD09GA surface reflectance data, a new MODIS snow-cover-extent (SCE) product from 2000 to 2020 over China has been
produced by the Northwest Institute of Eco-Environment and ...Resources
(NIEER), Chinese Academy of Sciences. The NIEER MODIS SCE product contains
two preliminary clear-sky SCE datasets – Terra-MODIS and Aqua-MODIS SCE
datasets and a final daily cloud-gap-filled (CGF) SCE dataset. The first two datasets are generated mainly through optimizing snow-cover discriminating rules over land-cover types, and the latter dataset is produced after a series of gap-filling
processes such as aggregating the two preliminary datasets, reducing cloud
gaps with adjacent information in space and time, and eliminating all gaps
with auxiliary data. The validation against 362 China Meteorological
Administration (CMA) stations shows that during snow seasons the overall
accuracy (OA) values of the three datasets are larger than 93 %, all of the omission error (OE) values are constrained within 9 %, and all of the commission error (CE) values are constrained within 10 %. Bias values of 0.98, 1.02, and 1.03 demonstrate on a whole that there is no significant overestimation nor a significant underestimation. Based on the same ground reference data, we found that the new product accuracies are obviously higher than standard MODIS snow products, especially for Aqua-MODIS and CGF SCE. For example, compared with the CE of 23.78 % that the MYD10A1 product shows, the CE of the new Aqua-MODIS SCE dataset is 6.78 %; the OA of the new CGF SCE dataset is up to 93.15 % versus 89.54 % of MOD10A1F product and 84.36 % of MYD10A1F product. Besides, as expected, snow discrimination in forest areas is also improved significantly. An isolated validation at four forest CMA stations demonstrates that the OA has increased by 3–10 percentage points, the OE has dropped by 1–8 percentage points, and the CE has dropped by 4–21 percentage points. Therefore, our product has virtually provided more reliable snow knowledge over China; thereby, it can better serve for hydrological, climatic, environmental, and other related studies there.
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