Effect of Consumer Characteristics on Benefit Sought and Importance of Attribute when New Product Introduction in Emerging Markets – Focused on Chinese Consumers -

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.

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Capacity Acquisition, Capacity Cost Allocation, and Pricing for New Product Introduction

SSRN Electronic Journal ◽

10.2139/ssrn.420781 ◽

2003 ◽

Author(s):

Birendra K. Mishra ◽

Ashutosh Prasad ◽

Dhinu Srinivasan

Keyword(s):

Cost Allocation ◽

New Product ◽

New Product Introduction ◽

Product Introduction ◽

Capacity Cost ◽

Capacity Acquisition

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A Bilingual Comparison of Sentiment and Topics for a Product Event on Twitter

Information Systems Frontiers ◽

10.1007/s10796-021-10169-x ◽

2021 ◽

Author(s):

Irina Wedel ◽

Michael Palk ◽

Stefan Voß

Keyword(s):

Social Media ◽

Language Processing ◽

Topic Modeling ◽

New Product ◽

Business Value ◽

Data Driven ◽

New Product Introduction ◽

Social Media Analytics ◽

Product Introduction ◽

Textual Data

AbstractSocial media enable companies to assess consumers’ opinions, complaints and needs. The systematic and data-driven analysis of social media to generate business value is summarized under the term Social Media Analytics which includes statistical, network-based and language-based approaches. We focus on textual data and investigate which conversation topics arise during the time of a new product introduction on Twitter and how the overall sentiment is during and after the event. The analysis via Natural Language Processing tools is conducted in two languages and four different countries, such that cultural differences in the tonality and customer needs can be identified for the product. Different methods of sentiment analysis and topic modeling are compared to identify the usability in social media and in the respective languages English and German. Furthermore, we illustrate the importance of preprocessing steps when applying these methods and identify relevant product insights.

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